Abstract
The number of accessible Web pages has been growing fast on the Internet. It has become increasingly difficult for users to find information on the Internet that satisfies their individual needs. This paper proposes a novel approach and presents a prototype system for personalized information retrieval based on user profile. In our system, we return different searching results to the same query according to each user’s profile. Compared with other personalized search systems, we learn the user profile automatically without any effort from the user. We use the method of support vector machine to construct user profile. A profile ontology is introduced in order to standardize the user profile and the raw results returned by the search engine wrapper. Experiments show that the precision of the returned web pages is effectively improved.
This work was supported by Nature Science Foundation of Anhui Province (No.050420305) and National “973” project (No. 2003CB317002).
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Song, R., Chen, E., Zhao, M. (2005). SVM Based Automatic User Profile Construction for Personalized Search. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_50
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DOI: https://doi.org/10.1007/11538059_50
Publisher Name: Springer, Berlin, Heidelberg
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