Abstract
In this paper, we propose a mining algorithm to utilize the user click-through data to improve search performance. The algorithm first explores the relationship between queries and Web pages and mine out co-visiting relationship as the virtual link among the Web pages, and then Spreading Activation mechanism is used to perform the query-dependent search. Our approach could overcome the challenges discussed above and the experimental results on a large set of MSN click-through log data show a significant improvement on search performance over the DirectHit algorithm as well as the baseline search engine.
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Xue, GR., Huang, S., Yu, Y., Zeng, HJ., Chen, Z., Ma, WY. (2004). Optimizing Web Search Using Spreading Activation on the Clickthrough Data. In: Zhou, X., Su, S., Papazoglou, M.P., Orlowska, M.E., Jeffery, K. (eds) Web Information Systems – WISE 2004. WISE 2004. Lecture Notes in Computer Science, vol 3306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30480-7_42
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DOI: https://doi.org/10.1007/978-3-540-30480-7_42
Publisher Name: Springer, Berlin, Heidelberg
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