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Email-based Intelligent Virtual Assistant (EIVA)

Email-based Intelligent Virtual Assistant (EIVA)

Anand Chowdhary's graduation project and thesis for Creative Technology Bsc at the University of Twente in Enschede, the Netherlands.

Anand Chowdhary

July 02, 2020
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  1. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  2. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  3. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  4. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  5. is a creative technologist and entrepreneur. Apart from studying CreaTe,

    he also co-founded Oswald Labs, an accessibility technology startup, for which he was featured in Forbes and Het Financieele Dagblad lists. He also studied at Santa Clara University as part of the Global Engineering Exchange program, and Bachelor Honors in Science at the UT. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  6. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  7. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  8. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands EIVA
  9. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  10. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and
  11. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and
  12. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and 8 out of 10 USE EMAIL FOR SCHEDULING
  13. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and 8 out of 10 USE EMAIL FOR SCHEDULING 6 out of 10 MEETINGS ARE RESCHEDULED
  14. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and 8 out of 10 USE EMAIL FOR SCHEDULING 6 out of 10 MEETINGS ARE RESCHEDULED €150 per month IN LOST TIME WHILE SCHEDULING
  15. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and
  16. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with
  17. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with
  18. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 9 out of 10 ASK ASSISTANT TO SCHEDULE
  19. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 9 out of 10 ASK ASSISTANT TO SCHEDULE 8 out of 10 AI ASSISTANT FOR SCHEDULING
  20. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 9 out of 10 ASK ASSISTANT TO SCHEDULE 8 out of 10 AI ASSISTANT FOR SCHEDULING THE SOLUTION?
  21. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with
  22. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  23. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  24. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood Florian Overkamp Founder of Speakup B.V.
  25. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood Idea Research Development External testing Analysis
  26. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  27. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  28. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  29. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  30. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  31. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  32. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  33. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  34. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood
  35. every month for professionals, because several email exchanges are required

    before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood SCREEN SHARING
  36. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared
  37. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared
  38. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing
  39. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction
  40. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction Intent Classification
  41. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction Intent Classification Date Parsing
  42. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction Intent Classification Date Parsing Google Cloud Natural Language API
  43. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction Intent Classification Date Parsing Google Cloud Natural Language API
  44. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction Intent Classification Date Parsing Google Cloud Natural Language API Node Natural with Naive Bayes Classifier natural
  45. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Language Detection & Variable Extraction Intent Classification Date Parsing Google Cloud Natural Language API Node Natural with Naive Bayes Classifier natural Chrono Node with custom filters Chrono
  46. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Natural Language Processing Intent Classification Node Natural with Naive Bayes Classifier natural
  47. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Intent Classification import { BayesClassifier } from "natural"; const classifier = new BayesClassifier(); classifier.addDocument( [ "set up an appointment", "schedule a call", "meet me for dinner", ], "setupNewAppointment" ); classifier.addDocument( [ "i can’t make it", "reschedule this call", "find another time", ], "rescheduleAppointment" ); classifier.train();
  48. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Intent Classification classifier.getClassifications( "i don’t think I’ll be able to make it to this time" ); // Classifications: // // setupNewAppointment: 0.1666 // rescheduleAppointment: 0.3333 // This never-before-seen sentence is correctly classified as ‘Reschedule Appointment’ This is an example with a tiny training dataset
  49. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared
  50. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared Configuration Management Transactional Emails Authentication Rate Limits MariaDB Redis ElasticSearch Simple Storage Service Public RESTful API Scheduled Jobs Third-party APIs Vue.js Nuxt.js Authorization in Fetching Unit Tests Continuous Integration Initialization Tests Uptime & Error Monitoring Sentry Resource Monitoring Caprover GitHub Actions Netlify Deployments
  51. and industry best-practices with the support of Speakup. Users can

    simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared
  52. scheduling preferences. A companion web application is also developed to

    manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  53. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  54. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. PROFESSIONALS OF PARTICIPANTS 18 employees at companies or organizations 9 students at schools or universities 3 self-employed professionals or freelancers
  55. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. 19,177 API requests 98 Emails processed 2,244 Pageviews
  56. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. Firefox Chrome Safari Safari Mobile Edge Chrome-related macOS Linux Windows Android iOS Ubuntu 992 529 377 217 83 44 772 729 637 59 3 34
  57. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. WEB APP EXPERIENCE 4.4 5.0 5.0 MEDIAN MODE MEAN WEB APP DESIGN 4.6 5.0 5.0 MEDIAN MODE MEAN
  58. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. WEB APP EXPERIENCE 4.4 5.0 5.0 MEDIAN MODE MEAN 4.6 5.0 5.0 MEDIAN MODE MEAN PRIVACY FEATURES 4.7 5.0 5.0 MEDIAN MODE MEAN WEB APP DESIGN
  59. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. ASSISTANT EXPERIENCE 4.5 5.0 5.0 MEDIAN MODE MEAN UNDERSTANDING 4.4 5.0 5.0 MEDIAN MODE MEAN
  60. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. TIME RECOMMENDATIONS 3.9 4.0 4.0 MEDIAN MODE MEAN TRUST 3.6 4.0 4.0 MEDIAN MODE MEAN
  61. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  62. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  63. preferences. A companion web application is also developed to manage

    meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  64. the average rating of the overall assistant and app experience

    of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  65. the average rating of the overall assistant and app experience

    of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. 29 out of 30 EIVA MET EXPECTATIONS
  66. the average rating of the overall assistant and app experience

    of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. 29 out of 30 EIVA MET EXPECTATIONS 25 out of 30 WOULD USE EIVA SERVICE
  67. the average rating of the overall assistant and app experience

    of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. 29 out of 30 EIVA MET EXPECTATIONS 25 out of 30 WOULD USE EIVA SERVICE 24 out of 30 WOULD PAY AT LEAST UP TO €5
  68. the average rating of the overall assistant and app experience

    of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  69. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  70. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  71. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. WHAT DO YOU LIKE THE MOST? 5 × Ease of use 3 × Fast response time 1 × Overall concept 1 × Security features 1 × Conversational interface 1 × Web app user interface
  72. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. WHAT DO YOU LIKE THE MOST? 5 × Ease of use 3 × Fast response time 1 × Overall concept 1 × Security features 1 × Conversational interface 1 × Web app user interface WHAT DO YOU LIKE THE LEAST? 1 × Pretending to be human 1 × Lengthy app onboarding 1 × Mobile user interface
  73. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers. WHAT DO YOU LIKE THE MOST? 5 × Ease of use 3 × Fast response time 1 × Overall concept 1 × Security features 1 × Conversational interface 1 × Web app user interface WHAT DO YOU LIKE THE LEAST? 1 × Pretending to be human 1 × Lengthy app onboarding 1 × Mobile user interface FEATURE RECOMMENDATIONS Meeting without emails SMS and WhatsApp support Multiple guests in a meeting Manual time slot selection Cancel or reschedule UI
  74. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  75. tracking. All but one participants said that the EIVA met

    their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  76. and 4.5 out of 5 respectively. Users’ behavior was also

    understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  77. A user experience evaluation of both the EIVA and its

    app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  78. Abstract Manually setting up appointments by email wastes tens of

    hours every month for professionals, because several email exchanges are required before receiving confirmation. Since not everyone can afford to hire full-time assistants, Email-based Intelligent Virtual Assistants (EIVA) can help by automating this task. In this paper, a functional EIVA is developed based on research and industry best-practices with the support of Speakup. Users can simply add their assistant’s address as ‘CC’ in an email, and EIVA will share the recommended location and time slots with guests, based on the user’s availability (using their calendar) and scheduling preferences. A companion web application is also developed to manage meetings and settings. The code is open source and written in TypeScript with Node.js and Vue.js and deployed on Amazon Web Services architecture in Europe. The product is built with focus on data privacy and user personalization. A user experience evaluation of both the EIVA and its app with 30 participants was conducted that found positive reception, with the average rating of the overall assistant and app experience of 4.4 and 4.5 out of 5 respectively. Users’ behavior was also understood with heatmaps and visualizations using pageview and mouse clicks tracking. All but one participants said that the EIVA met their expectations, and 25 out of 30 would use it in the future if it launches as a service. Most would also be willing to pay for it, with an average amount up to €6.16 per month. Participants also shared their frustrations and recommendations for future work. In the future, NLP classification should be improved and user recommendations should be implemented before launching the EIVA service for consumers.
  79. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands
  80. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands NOMINEE CREATIVE TECHNOLOGY BACHELOR AWARD UNIVERSITY OF TWENTE.
  81. How does the Naive Bayes Classifier actually work? What’s the

    author’s previous work, Ara? How did you collect data? How did you design the questions? How did you analyze the collected data? How did you capture stakeholders’ requirements? What questions did you explore using personas? How do you deal with gender bias in assistants? Do email recipients know EIVA is not human? How do you parse dates in emails? What authentications standards does the app use? Do you implement rate limits for security? How do you use scheduled jobs? How do you send client-side fetch requests? How do you manage state in the frontend app? Does EIVA work in both English and Dutch? How do you test the source code? How does the CI/CD pipeline work? How does you test external services? How much was the infrastructure cost? Do you monitor the service’s uptime? Do you monitor server resource usage? How do you know if an error occurs? Do people actually check their email or send emails? What calendaring services do people use? How many API requests or emails were logged? What were people’s first-impressions? How did people like the web app? How did people like the assistant over email? How much would people be willing to pay for this? What were common user frustrations? What were common feature recommendations? How would you improve this in the future? What about AI-driven job loss? What’s the business case for this service? How are the database tables structured? Where can I find the code for this?
  82. Email-based Intelligent Virtual Assistant for Scheduling Presented by Anand Chowdhary

    Supervised by Dr. Job Zwiers Creative Technology BSc University of Twente Enschede, the Netherlands