Abstract
With the fast development of World Wide Wed, web-based applications and services should allow users to get the right personalized information quickly and effectively. Collaborative Filtering plays a very important role in web service personalization and Recommender System. In this paper, Hesitation Degree was proposed to improve the accuracy of user based collaboration filtering and three kinds of Hesitation Degree were introduced into similarity computation. The results show that the prediction accuracy can be improved by 11 percents, and Mean Absolute Error can be reduced faster than classic method.
This work is supported by Research Fund for the Doctoral Program of Higher Education (No. 200801510001), the National Natural Science Foundation of China (70801007).
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Mu, X., Chen, Y., Yang, J., Jiang, J. (2010). An Improved Similarity Algorithm Based on Hesitation Degree for User-Based Collaborative Filtering. In: Cai, Z., Hu, C., Kang, Z., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2010. Lecture Notes in Computer Science, vol 6382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16493-4_27
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DOI: https://doi.org/10.1007/978-3-642-16493-4_27
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