A Novel Method for Clustering Web Search Results with Wikipedia Disambiguation Pages

Organizing search results of an ambiguous query into topics can facilitate information search on the Web. In this paper, we propose a novel method to cluster search results of ambiguous query into topics about the query constructed from Wikipedia disambiguation pages (WDP). To improve the clustering result, we propose a concept filtering method to filter semantically unrelated concepts in each topic. Also, we propose the top K full relations (TKFR) algorithm to assign search results to relevant topics based on the similarities between concepts in the results and topics. Comparing with the clustering methods whose topic labels are extracted from search results, the topics of WDP which are edited by human are much more helpful for navigation. The experiment results show that our method can work for ambiguous queries with different query lengths and highly improves the clustering result of method using WDP.

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