Upload
ysaidali
View
45
Download
0
Embed Size (px)
DESCRIPTION
Citation preview
Contextual Web Service
Suggest a query and a search engine
Aurélien Saint Requier, LITIS Rouen
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
Search the web
1.Select a search engine
2.Formulate your need3.Hope to find a relevant result in the result list
Select a search engine
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
Problems
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
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
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
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
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
From concepts to thematic profile
Profile fusion
●Function
Profile fusion
●Result
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
Translate keyword query to conceptual query
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>
Determine relevant search engine to the conceptual query (2)
●Use a similarity measure based on the types
and the categories of conceptual queries
Finaly
Finaly
Experimental system
●Based on WebLab and Liferay● Use Web services and portlet
Experimental system
●Based on WebLab and Liferay● Use Web services and portlet
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