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| Real-Time Search Suggestions Based on the Clustering of the User’ s Query Intent |
| Zhou Zhicheng |
| Shanghai Institute of Technology Library, Shanghai 200235, China |
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Abstract Aimed at the defects that the search engine offers too many results and is lack of considering the differences between the user’s personalities, this paper offers a way to give users real-time search suggestions of multi theme according to the user’s search intent in order to help the users describe the information in need more accurately, as well as narrow the gap between the query word and the user’s real intentions to increase the search efficiency. At the same time, it uses K-means to cluster users who are similar in their intent eigenvalue of resources categories, narrow the range of the nearest neighbor of the searching target, as well as to speed up the real-time response of the search suggestions. The experiment result shows that this method is practical.
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Received: 29 November 2010
Published: 25 March 2011
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