A Knowledge Base of Entity-Oriented Search Intents

Date: February 2nd, 2018
Venue: Stavanger, Norway. Technical talk at UiS TN-IDE

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#InformationRetrieval #IR #EntityOrientedSearch #EntityOrientedSearchIntents #KnowledgeBases

Transcript

1. A Knowledge Base of Entity-Oriented Search Intents Darío Garigliotti February 2, 2018
2. A brief introduction to... - Entities - Entity types - RDF tuples - Knowledge bases - Search intents
3. A brief introduction to... - Entities - Entity types - RDF tuples - Knowledge bases - Search intents
4. A brief introduction to... - Entities - Entity types - RDF tuples - Knowledge bases - Search intents
5. Recalling from the past
6. Recalling from the past
7. Entities - An entity is an individual or thing, uniquely identified - For example: Henrik Ibsen Stavanger - Also: Pythagorean Theorem UEFA Champions League
8. Entities
9. Entity types - A typical property of an entity is the type(s) - A entity type is a semantic class grouping multiple entities (Henrik Ibsen, is a, writer) (Henrik Ibsen, is a, Norwegian writer) (Henrik Ibsen, is a, person)
10. Entity types
11. Tuples - We describe entity properties using triples - Attributes (Henrik Ibsen, birthdate, 20 March 1828) - Types (Henrik Ibsen, is a, writer) - Relations (Henrik Ibsen, work, A Doll’s House) - RDF (Resource Description Framework) - A way to represent structured knowledge
12. Knowledge bases - A knowledge base (KB) is a set of tuples - There are many knowledge bases - Domain-specific, e.g. GeoNames, DOI, BBCMusic - Cross-domain, e.g. DBpedia, YAGO, Freebase, Google Knowledge Graph - Yes, there are many
13. Cloud of (linked) KBs
14. Search intents and refiners - Intent: the underlying user need in a search query - For example, the intent of booking a hotel room - Entity-oriented queries - Refiner: a way to express an intent in an entity- oriented query - For example, for booking a hotel room: "booking", "book", "reservation", "rooms"
15. Towards an understanding of search intents - A large proportion of entity-oriented search queries - Interest in understanding what those queries ask for, and how they can be fulfilled
16. A KB of entity-oriented search intents 1. Intents searched for a type of entities paris map, sydney map => [city] map - a 2. Categories assigned to refiners messi instagram => Website scandic rooms => Service henrik ibsen child => Property - a 3. Multiple refiners expressing an intent "booking", "book", "make a reservation", "rooms" - a
17. A KB of entity-oriented search intents 1. Intents searched for a type of entities paris map, sydney map => [city] map - (intent ID, searchedForType, entity type, conf.) 2. Categories assigned to refiners messi instagram => Website scandic rooms => Service henrik ibsen child => Property - a 3. Multiple refiners expressing an intent "booking", "book", "make a reservation", "rooms" - a
18. A KB of entity-oriented search intents 1. Intents searched for a type of entities paris map, sydney map => [city] map - (intent ID, searchedForType, entity type, conf.) 2. Categories assigned to refiners messi instagram => Website scandic rooms => Service henrik ibsen child => Property - (intent ID, ofCategory, intent category, conf.) 3. Multiple refiners expressing an intent "booking", "book", "make a reservation", "rooms" - a
19. A KB of entity-oriented search intents 1. Intents searched for a type of entities paris map, sydney map => [city] map - (intent ID, searchedForType, entity type, conf.) 2. Categories assigned to refiners messi instagram => Website scandic rooms => Service henrik ibsen child => Property - (intent ID, ofCategory, intent category, conf.) 3. Multiple refiners expressing an intent "booking", "book", "make a reservation", "rooms" - (intent ID, expressedBy, refiner, conf.)
20. Our pipeline approach
21. Our pipeline approach Entities: clarion hotel casa 400 ...
22. Our pipeline approach clarion hotel clarion hotel airport clarion hotel spa clarion hotel booking casa 400 casa 400 rooms casa 400 address casa 400 deals ...
23. Our pipeline approach clarion hotel clarion hotel airport clarion hotel spa clarion hotel booking casa 400 casa 400 rooms casa 400 address casa 400 deals clarion hotel airport casa 400 airport scandic airport ... ...
24. Our pipeline approach [hotel] airport clarion hotel clarion hotel airport clarion hotel spa clarion hotel booking casa 400 casa 400 rooms casa 400 address casa 400 deals clarion hotel airport casa 400 airport scandic airport ... ...
25. Our pipeline approach [hotel] airport [hotel] spa [hotel] booking ... clarion hotel clarion hotel airport clarion hotel spa clarion hotel booking casa 400 casa 400 rooms casa 400 address casa 400 deals clarion hotel airport casa 400 airport scandic airport ... ...
26. Our pipeline approach Refiners acquisition [hotel] airport [hotel] spa [hotel] booking ... clarion hotel clarion hotel airport clarion hotel spa clarion hotel booking casa 400 casa 400 rooms casa 400 address casa 400 deals clarion hotel airport casa 400 airport scandic airport ... ...
27. Our pipeline approach Refiners acquisition [hotel] airport [hotel] spa [hotel] booking ...
28. Our pipeline approach Refiners acquisition Refiners categorization [hotel] airport [hotel] spa [hotel] booking ...
29. Our pipeline approach Refiners acquisition Refiners categorization [hotel] airport [hotel] spa [hotel] booking ... [hotel] airport: Service [hotel] address: Property [hotel] expedia: Website ...
30. Our pipeline approach Refiners acquisition Refiners categorization Intents discovery [hotel] airport [hotel] spa [hotel] booking ... [hotel] airport: Service [hotel] address: Property [hotel] expedia: Website ...
31. Our pipeline approach Refiners acquisition Refiners categorization Intents discovery [hotel] airport [hotel] spa [hotel] booking ... [hotel] airport: Service [hotel] address: Property [hotel] expedia: Website ... taxi arrive Hotel_Arriving booking make a reservation Hotel_Booking address Hotel_Address
32. Our pipeline approach Refiners acquisition Refiners categorization Intents discovery [hotel] airport [hotel] spa [hotel] booking ... [hotel] airport: Service [hotel] address: Property [hotel] expedia: Website ... taxi arrive Hotel_Arriving booking make a reservation Hotel_Booking address Hotel_Address KB construction
33. Our pipeline approach Refiners acquisition Refiners categorization Intents discovery [hotel] airport [hotel] spa [hotel] booking ... [hotel] airport: Service [hotel] address: Property [hotel] expedia: Website ... taxi arrive Hotel_Arriving booking make a reservation Hotel_Booking address Hotel_Address Intent ID Predicate Object Confidence Hotel_Booking searchedForType [hotel] c1 Hotel_Booking ofCategory Service c2 Hotel_Booking expressedBy "booking" c3 Hotel_Booking expressedBy "make a reservation" c4 Hotel_Booking expressedBy "rooms" c5 KB construction
34. Our pipeline approach Refiners acquisition Refiners categorization Intents discovery [hotel] airport [hotel] spa [hotel] booking ... [hotel] airport: Service [hotel] address: Property [hotel] expedia: Website ... taxi arrive Hotel_Arriving booking make a reservation Hotel_Booking address Hotel_Address Intent profile { KB construction Intent ID Predicate Object Confidence Hotel_Booking searchedForType [hotel] c1 Hotel_Booking ofCategory Service c2 Hotel_Booking expressedBy "booking" c3 Hotel_Booking expressedBy "make a reservation" c4 Hotel_Booking expressedBy "rooms" c5
35. Evaluation - Component-level evaluation - Cross-validation using the human annotations of intent categories and refiner clusters, for a representative sample of 50 types - End-to-end evaluation - Human judgments about KB facts, for a sample of additional types, defined w.r.t. confidence intervals
36. Knowledge base construction - Application of the pipeline to extract all quadruples from 581 unseen types - 155K quadruples, 31K intent profiles Excerpt of the KB, for intent ID <aviation.airline-65-customer_service>
37. Results [0, 0.8652) [0.8652, 0.8837) [0.8837, 0.9043) [0.9043, 0.9319) [0.9319, 1] Confidence intervals according to the splitting percentiles 0% 20% 40% 60% 80% 100% Proportion of triples Correct Incorrect due to OFCATEGORY Incorrect due to EXPRESSEDBY
38. Application scenarios - Leveraging knowledge with levels of confidence - Identification of search intents in unseen queries - Design and functionality of entity cards
41. Thank you!