K. Murugan, S. Suma
We proposed a search engine that captures clickthrough data with time preferences which improves personalization more effective. User behavior is collected with content (user query), location (using GPS) and time of query. Timing information is collected so that user preference as per time is collected from that behavior of user is well known. GPCA algorithm is used for time information. Normally query result will be web popular result will present in top 100 results but user requested will be not get so user clicked data are stored as user preference and for future query result will be reranked with location, content and time. Ersonalization become more effective due to time in user behavior which makes system to understand what will be user requested and make ranking of resulted web page.
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