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Database Performance Tuning and Query Optimization Read chapter Read first chapter

2018 | OriginalPaper | Chapter

An Entropy-Based Similarity Measure for Collaborative Filtering

Author : Soojung Lee

Published in: Data Mining and Big Data

Publisher: Springer International Publishing

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Abstract

Collaborative filtering is a successfully utilized technique in many online commercial recommender systems. Similarity measures play an important role in this technique, as items preferred by similar users are to be recommended. Although various similarity measures have been developed, they usually treat each pair of user ratings separately or simply combine additional heuristic information with traditional similarity measures. This paper addresses this problem and suggests a new similarity measure which interprets user ratings in view of the global rating behavior on items by exploiting information entropy. Performance of the proposed measure is investigated through various experiments to find that it outperforms the existing similarity measures especially in a small-scaled sparse dataset.

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previous chapter Optimization Matrix Factorization Recommendation Algorithm Based on Rating Centrality
next chapter Three-Segment Similarity Measure Model for Collaborative Filtering
Literature
1.
Aamir, M., Bhusry, M.: Recommendation system: state of the art approach. Int. J. Comput. Appl. 120(12), 25–32 (2015)
2.
Bobadilla, J., Hernando, A., Ortega, F., Gutierrez, A.: Collaborative filtering based on significances. Inf. Sci. 185(1), 1–17 (2012)CrossRef
3.
Bobadilla, J., Ortega, F., Hernando, A.: A collaborative filtering similarity measure based on singularities. Inf. Process. Manage. 48(2), 204–217 (2012)CrossRef
4.
Bobadilla, J., Serradilla, F., Bernal, J.: A new collaborative filtering metric that improves the behavior of recommender systems. Knowl. Based Syst. 23(6), 520–528 (2010)CrossRef
5.
6.
Kwon, H.J., Lee, T.H., Kim, J.H., Hong, K.S.: Improving prediction accuracy using entropy weighting in collaborative filtering. In: Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, pp. 40–45 (2009)
7.
Jamali, M., Ester, M.: Trustwalker: a random walk model for combining trust-based and item-based recommendation. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 397–406. ACM (2009)
8.
Liu, H., Hu, Z., Mian, A., Tian, H., Zhu, X.: A new user similarity model to improve the accuracy of collaborative filtering. Knowl. Based Syst. 56, 156–166 (2014)CrossRef
9.
Piao, C.H., Zhao, J., Zheng, L.J.: Research on entropy-based collaborative filtering algorithm and personalized recommendation in e-commerce. Serv. Oriented Comput. Appl. 3(2), 147–157 (2009)CrossRef
10.
Ren, L., Gu, J., Xia, W.: A weighted similarity-boosted collaborative filtering approach. Energ. Proc. 13, 9060–9067 (2011)CrossRef
11.
Resnick, P., Lakovou, N., Sushak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings the ACM Conference on Computer Supported Cooperative Work, pp. 175–186. ACM Press (1994)
12.
Saranya, K.G., Sadasivam, G.S., Chandralekha, M.: Performance comparison of different similarity measures for collaborative filtering technique. Indian J. Sci. Technol. 9(29), 1–8 (2016)CrossRef
13.
Shannon, C.E.: Prediction and entropy of printed english. Bell Syst. Tech. J. 30, 50–64 (1951)CrossRef
14.
Su, X., Khoshgoftaar, T.M.: A survey of collaborative filtering techniques. Adv. Artif. Intell. 2009, 19 pages (2009). Article ID 421425
15.
Wang, W., Zhang, G., Lu, J.: Collaborative filtering with entropy-driven user similarity in recommender systems. Int. J. Intell. Syst. 30(8), 854–870 (2015)CrossRef
Metadata
Title
An Entropy-Based Similarity Measure for Collaborative Filtering
Author
Soojung Lee
Copyright Year
2018
Book
Data Mining and Big Data

Print ISBN: 978-3-319-93802-8

Electronic ISBN: 978-3-319-93803-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-93803-5_12

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