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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Online Clustering Algorithm for Restructuring User Web Search Results
verfasst von : M. Pavani, G. Ravi Teja
Erschienen in: Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014
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Now a day’s web mining is very important area. When user issues a query on the search engine, it gives relevant and irrelevant information to the user. If the query issued by the user is ambiguous then different users may get different search results and they have different search goals. The analysis of user search results according to their user goals can be very useful in improving search engine experience, usage and relevance. In this paper, we propose to infer user search goals by clustering the proposed user search sessions. User search sessions are constructed from user search logs and these can efficiently reflects the information needed by the users. An Online Clustering algorithm is used for clustering the pseudo documents, and then we use another appoarch to generate pseudo documents for better representation of the user search sessions for clustering. Finally we are using Classified Average Precision to evaluate the performance of inferring user search goals.