Context-aware web search using dynamically weighted information fusion

Authors


Correspondence to: Anderson, Nicole, Winona State University, Computer Science, P.O. Box 5838, Winona 55987, U.S.A.

E-mail: nanderson@winona.edu

SUMMARY

Web search has become a cornerstone tool for Internet users. The information one is able to retrieve quickly with commercial tools is awe inspiring, yet average users still remain frustrated with finding information that is truly relevant to them. In our research, we seek to show that if we utilize key pieces of information about a user and their current context, we can provide more accurate results. We do this by exploring context data, using query enhancement techniques, and appropriately fusing the results to provide the best ordering when presenting the results to the user. Context data includes a user's personal calendar, location, preferences, personal vocabulary, and peer recommendations. Query enhancement involves utilizing relevant contextual information to decorate a user's query text to produce a more focused query. Information fusion allows the query results to be compared and re-ordered using contextual data by utilizing either a sum of products, a Bayesian technique, or a combination of the two. We find that by combining these methods, we are able to significantly enhance the search results. We have performed a case study and present the results here. Copyright © 2011 John Wiley & Sons, Ltd.

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