Personalized Concept-Based Clustering of Search Engine Queries

A major problem of current Web search is that search queries are usually short and ambiguous, and thus are insufficient for specifying the precise user needs. To alleviate this problem, some search engines suggest terms that are semantically related to the submitted queries so that users can choose from the suggestions the ones that reflect their information needs. In this paper, we introduce an effective approach that captures the user's conceptual preferences in order to provide personalized query suggestions. We achieve this goal with two new strategies. First, we develop online techniques that extract concepts from the web-snippets of the search result returned from a query and use the concepts to identify related queries for that query. Second, we propose a new twophase personalized agglomerative clustering algorithm that is able to generate personalized query clusters. To the best of the authors' knowledge, no previous work has addressed personalization for query sugges...

• Type: Journal
• Year: 2008
• Where: TKDE
• Authors: Kenneth Wai-Ting Leung, Wilfred Ng, Dik Lun Lee
• Keywords: Current Web Search, Major Problem, Query Suggestions, TKDE 2008