rise 2014 st requier
DESCRIPTION
TRANSCRIPT
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Contextual Web Service
Suggest a query and a search engine
Aurélien Saint Requier, LITIS Rouen
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Table of contents
� What is search on the Internet?What is search on the Internet?What is search on the Internet?What is search on the Internet?� Our proposal
● Modelize user interests● Suggest pairs of conceptual query and search engine
� Evaluation� Conclusion
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Search the web
1.Select a search engine
2.Formulate your need3.Hope to find a relevant result in the result list
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Select a search engine
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Formulate a need
➔Users express query in few words (2-3)➔Between 20% and 30% of queries contain a
single word➔Users often reformulate their queries➔For novice users, the formulation of queries
is a difficult task➔For a complex information task, users
formulate more and longer queries in a same
session
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Problems
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Analyze results
➔Users show interest on the first and second
results➔Users do not go beyond the first result page➔For a complex information task, users spend
more time on the result page
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Proposal
Goal: ➔Help the user to formulate his need and
suggest a search engine according to his
need
How:➔Get interests of users➔Suggest a pair composed of a conceptual
query and a search engine
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Get interests of a user
➔Use a weighted conceptual user profile: ● a long term profile = knowledge of the user● a short term profile = context of the search
➔Corpus:● LP : web pages mark as favorite, saved web pages and
documents provide by users to avoid cold start problem.● SP : all visited web pages
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Get interests of a user
➔Represent an interest by a DBPedia category➔Weight is equal to the probability of
occurrence of the concept in the corpus
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Technical issues to profile construction
●Use Zemanta to extract DBPedia concepts
from text●Encode profile in Attention Profiling Markup
Language (APML)●Develop a Firefox extension to track user web
activities
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From concepts to thematic profile
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Profile fusion
●Function
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Profile fusion
●Result
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Suggest pairs of conceptual query and search engine
Process :
1.Get keyword user query2.Translate keyword query in conceptual
queries
3.Match conceptual queries with search
engines
4.Suggest pairs of conceptual query and search engines
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Translate keyword query to conceptual query
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Determine relevant search engine to the conceptual query (1)
●Define a semantic description of a Search
Engine : <SearchEngine> <Id>e018</Id> <Name>LastFM</Name> <Url>http://www.lastfm.fr/music/</Url> <Description>Last.fm is a music recommendation service. </Description> <Specialized>true</Specialized> <Thematic> <Subject> … </Subject> </Thematic> <ContentType> <Type>http://dbpedia.org/ontology/Band</Type> <Type>http://dbpedia.org/ontology/Single</Type> <Type>http://dbpedia.org/ontology/MusicalWork</Type> <Type>http://dbpedia.org/ontology/Album</Type> </ContentType> <Popularity>5</Popularity> <Searchable>true</Searchable></SearchEngine>
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Determine relevant search engine to the conceptual query (2)
●Use a similarity measure based on the types
and the categories of conceptual queries
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Finaly
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Finaly
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Experimental system
●Based on WebLab and Liferay● Use Web services and portlet
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Experimental system
●Based on WebLab and Liferay● Use Web services and portlet
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Conclusion
� Modelize user interests by a thematic profile� Use this thematic profile to translate keyword queries into conceptual queries
� Suggest pairs of conceptual query and search engine
� Upcoming evaluation● Compare our approach of (conceptual query / search
engine) pair suggestion to (google suggestion / google
search engine) pair suggestion