Semantic Web Dog Food

Presented at: 20th International World Wide Web Conference (WWW2011)

by Gabriele Capannini, Franco Maria Nardini, Raffaele Perego, Fabrizio Silvestri

We study the problem of diversifying search results by exploiting the knowledge mined from query logs. Our proposal exploits the presence of different "specializations" of queries in query logs to detect the submission of ambiguous/faceted queries, and manage them by diversifying the search results returned in order to cover the different possible interpretations of the query. We present an original formulation of the results diversification problem in terms of an objective function to be maximized that admits the finding of an optimal solution in linear time.

Efficient Diversification of Search Results Using Query Logs was presented at this event.

Keywords: World Wide Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2011/poster/efficient-diversification-of-search-results-using-

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