the customer information on all the hotels that traditionally only a travel agent would have access to, and this is done via an easy to use website. There is one big restriction, it still requires someone to know where and when they will be going, which does not suit a lot of people, as often what we are really looking for is a theme, or an activity rather than an exact location. We want to be able to offer a more natural way searching, so instead of filling in a form with the where, when and who, or typing “Hotel, Paris” in a search engine and then actually fill out the details. We want to be able offer somewhere you can express your desire to “maybe visit Paris for a weekend”, or a “relax on the beach” and get some relevant and interesting results.
because firstly we need to get computers to understand how people express their intention, through writing, which its not something machines traditionally do very well. How there is a way, NLP, not the psychology field of Neuro Linguistic Programming. Rather Natural Language Processing (which is the field of computer science that deals with understanding human text, mainly through machine learning.) We are using Stanford university’s offering as the basis for a solution. Lets go in to some detail of how the Natural Language Processing or NLP works by looking at what is actually does, concentrating on the parts most useful for our searching problem, the most relevant elements are it’s ability to identify semantic structure of sentences as this is the foundation for then recognizing entities plus can also help with identifying
because firstly we need to get computers to understand how people express their intention, through writing, which its not something machines traditionally do very well. How there is a way, NLP, not the psychology field of Neuro Linguistic Programming. Rather Natural Language Processing (which is the field of computer science that deals with understanding human text, mainly through machine learning.) We are using Stanford university’s offering as the basis for a solution. Lets go in to some detail of how the Natural Language Processing or NLP works by looking at what is actually does, concentrating on the parts most useful for our searching problem, the most relevant elements are it’s ability to identify semantic structure of sentences as this is the foundation for then recognizing entities plus can also help with identifying
because firstly we need to get computers to understand how people express their intention, through writing, which its not something machines traditionally do very well. How there is a way, NLP, not the psychology field of Neuro Linguistic Programming. Rather Natural Language Processing (which is the field of computer science that deals with understanding human text, mainly through machine learning.) We are using Stanford university’s offering as the basis for a solution. Lets go in to some detail of how the Natural Language Processing or NLP works by looking at what is actually does, concentrating on the parts most useful for our searching problem, the most relevant elements are it’s ability to identify semantic structure of sentences as this is the foundation for then recognizing entities plus can also help with identifying
for a weekend” (IN) (DT) (NN) The first part of NLP I will focus on is Part of Speech tagging, which means it is going to take some text, for example this simple phase, “I want to go to Paris” then break it down in to separate tokens (usually a word) and based on its definition and its context (i.e. relationship with near by words) mark each word with a part of speech definition. Once the phrase has been tagged, you can see “I” as a preposition, “want” is a verb, to is a “TO” (still not really sure what that is), “visit” is another verb and “Paris” a “proper noun”. If we extend out the phrase a little to add “for a weekend”. And tag it once again, you can see it makes “for” an different type of preposition, “a” determiner and “weekend” a noun. This is something similar to what they tried to teach most of us at school with the noun, adjective, verbs etc. However being dyslexic I never really had any clue what any of this meant. All very technical but its not obvious how we can use any of
for a weekend” (IN) (DT) (NN) The first part of NLP I will focus on is Part of Speech tagging, which means it is going to take some text, for example this simple phase, “I want to go to Paris” then break it down in to separate tokens (usually a word) and based on its definition and its context (i.e. relationship with near by words) mark each word with a part of speech definition. Once the phrase has been tagged, you can see “I” as a preposition, “want” is a verb, to is a “TO” (still not really sure what that is), “visit” is another verb and “Paris” a “proper noun”. If we extend out the phrase a little to add “for a weekend”. And tag it once again, you can see it makes “for” an different type of preposition, “a” determiner and “weekend” a noun. This is something similar to what they tried to teach most of us at school with the noun, adjective, verbs etc. However being dyslexic I never really had any clue what any of this meant. All very technical but its not obvious how we can use any of
(NNP) for a weekend” (IN) (DT) (NN) The first part of NLP I will focus on is Part of Speech tagging, which means it is going to take some text, for example this simple phase, “I want to go to Paris” then break it down in to separate tokens (usually a word) and based on its definition and its context (i.e. relationship with near by words) mark each word with a part of speech definition. Once the phrase has been tagged, you can see “I” as a preposition, “want” is a verb, to is a “TO” (still not really sure what that is), “visit” is another verb and “Paris” a “proper noun”. If we extend out the phrase a little to add “for a weekend”. And tag it once again, you can see it makes “for” an different type of preposition, “a” determiner and “weekend” a noun. This is something similar to what they tried to teach most of us at school with the noun, adjective, verbs etc. However being dyslexic I never really had any clue what any of this meant. All very technical but its not obvious how we can use any of
(NNP) for a weekend” (IN) (DT) (NN) The first part of NLP I will focus on is Part of Speech tagging, which means it is going to take some text, for example this simple phase, “I want to go to Paris” then break it down in to separate tokens (usually a word) and based on its definition and its context (i.e. relationship with near by words) mark each word with a part of speech definition. Once the phrase has been tagged, you can see “I” as a preposition, “want” is a verb, to is a “TO” (still not really sure what that is), “visit” is another verb and “Paris” a “proper noun”. If we extend out the phrase a little to add “for a weekend”. And tag it once again, you can see it makes “for” an different type of preposition, “a” determiner and “weekend” a noun. This is something similar to what they tried to teach most of us at school with the noun, adjective, verbs etc. However being dyslexic I never really had any clue what any of this meant. All very technical but its not obvious how we can use any of
(NNP) for a weekend” (IN) (DT) (NN) The first part of NLP I will focus on is Part of Speech tagging, which means it is going to take some text, for example this simple phase, “I want to go to Paris” then break it down in to separate tokens (usually a word) and based on its definition and its context (i.e. relationship with near by words) mark each word with a part of speech definition. Once the phrase has been tagged, you can see “I” as a preposition, “want” is a verb, to is a “TO” (still not really sure what that is), “visit” is another verb and “Paris” a “proper noun”. If we extend out the phrase a little to add “for a weekend”. And tag it once again, you can see it makes “for” an different type of preposition, “a” determiner and “weekend” a noun. This is something similar to what they tried to teach most of us at school with the noun, adjective, verbs etc. However being dyslexic I never really had any clue what any of this meant. All very technical but its not obvious how we can use any of
(NNP) for a weekend ” (IN) (DT) (NN) The first part of NLP I will focus on is Part of Speech tagging, which means it is going to take some text, for example this simple phase, “I want to go to Paris” then break it down in to separate tokens (usually a word) and based on its definition and its context (i.e. relationship with near by words) mark each word with a part of speech definition. Once the phrase has been tagged, you can see “I” as a preposition, “want” is a verb, to is a “TO” (still not really sure what that is), “visit” is another verb and “Paris” a “proper noun”. If we extend out the phrase a little to add “for a weekend”. And tag it once again, you can see it makes “for” an different type of preposition, “a” determiner and “weekend” a noun. This is something similar to what they tried to teach most of us at school with the noun, adjective, verbs etc. However being dyslexic I never really had any clue what any of this meant. All very technical but its not obvious how we can use any of
Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt was on hand to premiere his new film, Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt Cannes Film Festival France Organisation Person Location Interesting no doubt, but I need something more, what I really wanted was a way of extracting entities with their type and value. With this I would be able to take the information and later use it in a search. Welcome to Named Entity Recognizer, which will basically tell me who’s who and what’s what. A little example of this can demonstrate why I was so excited about Named Entity Recognition, as you can see from the sample news extract. The results after applying the named entity recognizer to it were as follows. It identified Brad Pitt as a person, Cannes Film festival as and organization and France as a places. Which is great I can look all these entities up in a database later and get additional information about them.
Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt was on hand to premiere his new film, Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt Cannes Film Festival France Organisation Person Location Interesting no doubt, but I need something more, what I really wanted was a way of extracting entities with their type and value. With this I would be able to take the information and later use it in a search. Welcome to Named Entity Recognizer, which will basically tell me who’s who and what’s what. A little example of this can demonstrate why I was so excited about Named Entity Recognition, as you can see from the sample news extract. The results after applying the named entity recognizer to it were as follows. It identified Brad Pitt as a person, Cannes Film festival as and organization and France as a places. Which is great I can look all these entities up in a database later and get additional information about them.
Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt was on hand to premiere his new film, Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt Cannes Film Festival France Organisation Person Location Interesting no doubt, but I need something more, what I really wanted was a way of extracting entities with their type and value. With this I would be able to take the information and later use it in a search. Welcome to Named Entity Recognizer, which will basically tell me who’s who and what’s what. A little example of this can demonstrate why I was so excited about Named Entity Recognition, as you can see from the sample news extract. The results after applying the named entity recognizer to it were as follows. It identified Brad Pitt as a person, Cannes Film festival as and organization and France as a places. Which is great I can look all these entities up in a database later and get additional information about them.
Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt was on hand to premiere his new film, Killing Them Softly, Tuesday afternoon at the 2012 Cannes Film Festival, in France. Brad Pitt Cannes Film Festival France Organisation Person Location Interesting no doubt, but I need something more, what I really wanted was a way of extracting entities with their type and value. With this I would be able to take the information and later use it in a search. Welcome to Named Entity Recognizer, which will basically tell me who’s who and what’s what. A little example of this can demonstrate why I was so excited about Named Entity Recognition, as you can see from the sample news extract. The results after applying the named entity recognizer to it were as follows. It identified Brad Pitt as a person, Cannes Film festival as and organization and France as a places. Which is great I can look all these entities up in a database later and get additional information about them.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Now if we try the same thing with our phrase for Paris, the results are more frustrating it discovered Paris was a place, but ignored romantic and weekend. Basically the default is to recognize only places, people and organizations as it has been trained to recognize these within large corpuses of text.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Now if we try the same thing with our phrase for Paris, the results are more frustrating it discovered Paris was a place, but ignored romantic and weekend. Basically the default is to recognize only places, people and organizations as it has been trained to recognize these within large corpuses of text.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Now if we try the same thing with our phrase for Paris, the results are more frustrating it discovered Paris was a place, but ignored romantic and weekend. Basically the default is to recognize only places, people and organizations as it has been trained to recognize these within large corpuses of text.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Now if we try the same thing with our phrase for Paris, the results are more frustrating it discovered Paris was a place, but ignored romantic and weekend. Basically the default is to recognize only places, people and organizations as it has been trained to recognize these within large corpuses of text.
retrain it on travel specific terms, with short phrases to look for entities like, places, activities, themes. An important note about training is that, it should be trained on text similar to what you want it later interpret. So training it on text from Shakespeare will make it excellent at understanding plays from the Elizabethan era but not useful at knowing where we want to go on holiday.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
wellness centre. Where is good to take a city break? I want to go skiing or snow boarding in the Alps. Where can I go rock climbing in Malta? Finding this relevant text was a challenge so we turned to amazon and mechanical turk to get lots of phrases people would write when asking for a holiday. We used most of it for training but kept back some for testing and validation purposes. Training is achieved by taking some text and tagging the location and boundary of the entity you are interested in. The data was tagged with entity types of place/attraction, theme/activity and or amenity.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Theme Temporal We were able to get take the previous phrase “I want to visit Paris for a Romantic weekend” and identify that Paris is a location and that romantic is a theme. With regards to weekend, we will actually use something called temporal tagging that is specifically designed to understand dates and ranges.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Theme Temporal We were able to get take the previous phrase “I want to visit Paris for a Romantic weekend” and identify that Paris is a location and that romantic is a theme. With regards to weekend, we will actually use something called temporal tagging that is specifically designed to understand dates and ranges.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Theme Temporal We were able to get take the previous phrase “I want to visit Paris for a Romantic weekend” and identify that Paris is a location and that romantic is a theme. With regards to weekend, we will actually use something called temporal tagging that is specifically designed to understand dates and ranges.
want to visit Paris for a romantic weekend. Paris romantic weekend Location Theme Temporal We were able to get take the previous phrase “I want to visit Paris for a Romantic weekend” and identify that Paris is a location and that romantic is a theme. With regards to weekend, we will actually use something called temporal tagging that is specifically designed to understand dates and ranges.
How did it know when we are referring to a “place”, and what was an “activity”? It uses machine learning to look for patterns, the input for this are training files, they contain the data that will used to establish the patterns. One example is sentence structure, it will look 3-4 words backwards and perhaps 1-2 forwards to see if it is expecting an entity. A simple example of this can “Goodmans” its difficult to know that that is, partly because I made it up for this presentation. But if I said “I am going to eat at Goodmans tonight” we can
How did it know when we are referring to a “place”, and what was an “activity”? It uses machine learning to look for patterns, the input for this are training files, they contain the data that will used to establish the patterns. One example is sentence structure, it will look 3-4 words backwards and perhaps 1-2 forwards to see if it is expecting an entity. A simple example of this can “Goodmans” its difficult to know that that is, partly because I made it up for this presentation. But if I said “I am going to eat at Goodmans tonight” we can
How did it know when we are referring to a “place”, and what was an “activity”? It uses machine learning to look for patterns, the input for this are training files, they contain the data that will used to establish the patterns. One example is sentence structure, it will look 3-4 words backwards and perhaps 1-2 forwards to see if it is expecting an entity. A simple example of this can “Goodmans” its difficult to know that that is, partly because I made it up for this presentation. But if I said “I am going to eat at Goodmans tonight” we can
uses is word structure, not only the length but also makeup of a word, this can commonly be seen in place names like Ireland, Greenland, England, they all have the land part to them. More so with activities skiing, sailing, hiking, etc. Now these are extreme examples in that I dont know any places ending with “ing” or activities with “land” but it will combine results from both word and sentence structure to make a best guess.
uses is word structure, not only the length but also makeup of a word, this can commonly be seen in place names like Ireland, Greenland, England, they all have the land part to them. More so with activities skiing, sailing, hiking, etc. Now these are extreme examples in that I dont know any places ending with “ing” or activities with “land” but it will combine results from both word and sentence structure to make a best guess.
Another method it uses is word structure, not only the length but also makeup of a word, this can commonly be seen in place names like Ireland, Greenland, England, they all have the land part to them. More so with activities skiing, sailing, hiking, etc. Now these are extreme examples in that I dont know any places ending with “ing” or activities with “land” but it will combine results from both word and sentence structure to make a best guess.
Another method it uses is word structure, not only the length but also makeup of a word, this can commonly be seen in place names like Ireland, Greenland, England, they all have the land part to them. More so with activities skiing, sailing, hiking, etc. Now these are extreme examples in that I dont know any places ending with “ing” or activities with “land” but it will combine results from both word and sentence structure to make a best guess.
windows Average Weekend trips 24 18 Days So now we have our sentence tagged, but we have some missing gaps, we have a location, some requirements for the hotels, and half a date. (We more or less know the duration, its saturday to sunday but not the when...yet) This basically happened because we have no control over what people write, after all its an open search. Although we can look at our booking history and find out typically how far in advance do people book trips i.e. the booking window. On average it is about 24 days. So we should start looking for something how far in advance do people book trips for 2 days, so we should look for departure times on the 29th of this month. However for weekend trips, i.e. 2 days. This is 18 days, so that brings suggests the departing on the 22nd will make more sense. Also its worth noting, that the average booking for trips of a
windows Average Weekend trips 24 18 Days So now we have our sentence tagged, but we have some missing gaps, we have a location, some requirements for the hotels, and half a date. (We more or less know the duration, its saturday to sunday but not the when...yet) This basically happened because we have no control over what people write, after all its an open search. Although we can look at our booking history and find out typically how far in advance do people book trips i.e. the booking window. On average it is about 24 days. So we should start looking for something how far in advance do people book trips for 2 days, so we should look for departure times on the 29th of this month. However for weekend trips, i.e. 2 days. This is 18 days, so that brings suggests the departing on the 22nd will make more sense. Also its worth noting, that the average booking for trips of a
windows Average Weekend trips 24 18 Days So now we have our sentence tagged, but we have some missing gaps, we have a location, some requirements for the hotels, and half a date. (We more or less know the duration, its saturday to sunday but not the when...yet) This basically happened because we have no control over what people write, after all its an open search. Although we can look at our booking history and find out typically how far in advance do people book trips i.e. the booking window. On average it is about 24 days. So we should start looking for something how far in advance do people book trips for 2 days, so we should look for departure times on the 29th of this month. However for weekend trips, i.e. 2 days. This is 18 days, so that brings suggests the departing on the 22nd will make more sense. Also its worth noting, that the average booking for trips of a
windows Average Weekend trips 24 18 Days So now we have our sentence tagged, but we have some missing gaps, we have a location, some requirements for the hotels, and half a date. (We more or less know the duration, its saturday to sunday but not the when...yet) This basically happened because we have no control over what people write, after all its an open search. Although we can look at our booking history and find out typically how far in advance do people book trips i.e. the booking window. On average it is about 24 days. So we should start looking for something how far in advance do people book trips for 2 days, so we should look for departure times on the 29th of this month. However for weekend trips, i.e. 2 days. This is 18 days, so that brings suggests the departing on the 22nd will make more sense. Also its worth noting, that the average booking for trips of a
windows Average Weekend trips 24 18 Days So now we have our sentence tagged, but we have some missing gaps, we have a location, some requirements for the hotels, and half a date. (We more or less know the duration, its saturday to sunday but not the when...yet) This basically happened because we have no control over what people write, after all its an open search. Although we can look at our booking history and find out typically how far in advance do people book trips i.e. the booking window. On average it is about 24 days. So we should start looking for something how far in advance do people book trips for 2 days, so we should look for departure times on the 29th of this month. However for weekend trips, i.e. 2 days. This is 18 days, so that brings suggests the departing on the 22nd will make more sense. Also its worth noting, that the average booking for trips of a
want to visit Paris for a weekend. Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun Something really important to note is that while NLP can assist in interpreting intention from a phrase, it will do it very literally. But people have a habit of not always saying exactly what they mean, take the phrase “I want to visit to Paris for the weekend” so here we probably talking about a quick eurostar trip leaving early saturday and returning sunday sometime. But now contrast this with the phrase “I want to visit New York for the weekend” is that literally what someone really wants especially someone leaving from london. Due to the distance they are problably thinking of more a thurs - mon rather than a sat-sun. Again we have some figures to back this up, so we will do our searching to represent this.
want to visit Paris for a weekend. Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun Something really important to note is that while NLP can assist in interpreting intention from a phrase, it will do it very literally. But people have a habit of not always saying exactly what they mean, take the phrase “I want to visit to Paris for the weekend” so here we probably talking about a quick eurostar trip leaving early saturday and returning sunday sometime. But now contrast this with the phrase “I want to visit New York for the weekend” is that literally what someone really wants especially someone leaving from london. Due to the distance they are problably thinking of more a thurs - mon rather than a sat-sun. Again we have some figures to back this up, so we will do our searching to represent this.
want to visit Paris for a weekend. Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun Something really important to note is that while NLP can assist in interpreting intention from a phrase, it will do it very literally. But people have a habit of not always saying exactly what they mean, take the phrase “I want to visit to Paris for the weekend” so here we probably talking about a quick eurostar trip leaving early saturday and returning sunday sometime. But now contrast this with the phrase “I want to visit New York for the weekend” is that literally what someone really wants especially someone leaving from london. Due to the distance they are problably thinking of more a thurs - mon rather than a sat-sun. Again we have some figures to back this up, so we will do our searching to represent this.
want to visit Paris for a weekend. Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun Something really important to note is that while NLP can assist in interpreting intention from a phrase, it will do it very literally. But people have a habit of not always saying exactly what they mean, take the phrase “I want to visit to Paris for the weekend” so here we probably talking about a quick eurostar trip leaving early saturday and returning sunday sometime. But now contrast this with the phrase “I want to visit New York for the weekend” is that literally what someone really wants especially someone leaving from london. Due to the distance they are problably thinking of more a thurs - mon rather than a sat-sun. Again we have some figures to back this up, so we will do our searching to represent this.
want to visit Paris for a weekend. Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun Something really important to note is that while NLP can assist in interpreting intention from a phrase, it will do it very literally. But people have a habit of not always saying exactly what they mean, take the phrase “I want to visit to Paris for the weekend” so here we probably talking about a quick eurostar trip leaving early saturday and returning sunday sometime. But now contrast this with the phrase “I want to visit New York for the weekend” is that literally what someone really wants especially someone leaving from london. Due to the distance they are problably thinking of more a thurs - mon rather than a sat-sun. Again we have some figures to back this up, so we will do our searching to represent this.
questions Firstly, do people want it, after all we seam ok with the current tools? Yes I guess so, we are, but also there are already steps being made in the direction of themed searching and more more people are looking to natural ways of communicating with technology. Then, “Can it work?” Apart from answering with thanks for the faith colleagues. Perhaps a more sensible answer would be, never 100% but by learning, using the phrases people give us to improve the training files and making better use of the statistics, there is no reason why it can not give excellent results. Plus I am still in my probation so I really need it to work. Improvements
of where we want to be. Instead of restricting someone to having to “Specify they want to go to Malaga” which would put them about here. Lets make it more open and natural, after all is there REALLY a requirement of Malaga or they just asking for sun, sand, seafood and bars. Would not somewhere like Soller (still Spain) or Praia da rocha (portugal), or any of these other places be just as good or perhaps better. We can give people more adventure than just
of where we want to be. Instead of restricting someone to having to “Specify they want to go to Malaga” which would put them about here. Lets make it more open and natural, after all is there REALLY a requirement of Malaga or they just asking for sun, sand, seafood and bars. Would not somewhere like Soller (still Spain) or Praia da rocha (portugal), or any of these other places be just as good or perhaps better. We can give people more adventure than just
of where we want to be. Instead of restricting someone to having to “Specify they want to go to Malaga” which would put them about here. Lets make it more open and natural, after all is there REALLY a requirement of Malaga or they just asking for sun, sand, seafood and bars. Would not somewhere like Soller (still Spain) or Praia da rocha (portugal), or any of these other places be just as good or perhaps better. We can give people more adventure than just
of where we want to be. Instead of restricting someone to having to “Specify they want to go to Malaga” which would put them about here. Lets make it more open and natural, after all is there REALLY a requirement of Malaga or they just asking for sun, sand, seafood and bars. Would not somewhere like Soller (still Spain) or Praia da rocha (portugal), or any of these other places be just as good or perhaps better. We can give people more adventure than just
of where we want to be. Instead of restricting someone to having to “Specify they want to go to Malaga” which would put them about here. Lets make it more open and natural, after all is there REALLY a requirement of Malaga or they just asking for sun, sand, seafood and bars. Would not somewhere like Soller (still Spain) or Praia da rocha (portugal), or any of these other places be just as good or perhaps better. We can give people more adventure than just
of where we want to be. Instead of restricting someone to having to “Specify they want to go to Malaga” which would put them about here. Lets make it more open and natural, after all is there REALLY a requirement of Malaga or they just asking for sun, sand, seafood and bars. Would not somewhere like Soller (still Spain) or Praia da rocha (portugal), or any of these other places be just as good or perhaps better. We can give people more adventure than just
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