Abstract
Personalized web search according to user’s geographic and temporal preferences can improve search results quality and satisfy user’s different information needs. We propose a novel approach to capture user’s geographic and temporal preferences in the form of query profile and user preference profile by mining search results and user click-through data leveraging knowledge bases. Our approach classifies queries into five classes based on decision tree algorithm. When personalizing search results, different weights are set to different query classes to balance among content, geographic and temporal information associated with a query. The experiment evaluation results show the effectiveness of our approach and improvement of the search quality.
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Yang, D., Nie, T., Shen, D., Yu, G., Kou, Y. (2011). Personalized Web Search with User Geographic and Temporal Preferences. In: Du, X., Fan, W., Wang, J., Peng, Z., Sharaf, M.A. (eds) Web Technologies and Applications. APWeb 2011. Lecture Notes in Computer Science, vol 6612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20291-9_12
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DOI: https://doi.org/10.1007/978-3-642-20291-9_12
Publisher Name: Springer, Berlin, Heidelberg
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