Abstract
Data sparsity is a main factor affecting the prediction accuracy of collaborative filtering. Based on the simple linear regression model, Slope One algorithm aims to enhance the performance significantly by reducing the response time and maintenance, and overcoming the cold start issue. It uses rating data to do calculation without considering the similarity. In this paper, we proposed an improved algorithm by combining the dynamic k-nearest-neighborhood method and the user similarity generated by the weighted information entropy with Slope One algorithm. Especially, the similarity between users is calculated and added on the fly. Experiments on the MovieLens data set show that the proposed algorithm can achieve better recommendation quality and prediction accuracy. Besides, the stability of the algorithm is also relatively satisfying.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Xu, H.L., Wu, X., Li, X.D., Yan, B.P.: Comparison study of Internet recommendation system. J. Software 20(2), 350–362 (2009)
Herlocker, J., Konstan, J.A., Riedl, J.: An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms. Inf. Retrieval 5(4), 287–310 (2002)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp. 285–295. ACM (2001)
Huang, C.G., Yin, J., Wang, J., Liu, Y.B., Wang, J.H.: Uncertain neighbors’ collaborative filtering recommendation algorithm. Jisuanji Xuebao (Chin. J. Comput.) 33(8), 1369–1377 (2010)
Lemire, D., Maclachlan, A.: Slope One predictors for online rating-based collaborative filtering. SDM 5, 1–5 (2005)
Pang, H., Zhou, L., Liu, H.: Personalization portal system based on collaborative filtering algorithm. In: Computer, Mechatronics, Control and Electronic Engineering (CMCE), vol. 1, pp. 383–386. IEEE (2010)
Du, M., Liu, M., Li, S., Pu, Q.: Slope One collaborative filtering algorithm based on neighboring items. J. Chongqing Univ. Posts: Telecommun. Nat. Sci. Ed. 26(3), 421–426 (2014)
Lin, D.J., Meng, X.W.: Slope One algorithm based on single value decomposition. New Type Industrialization 2(11), 12–17 (2012)
Luo, L., Xie, Y., Zhang, Z., Li, W.J.: Support matrix machines. In: Proceedings of the 32nd International Conference on Machine Learning (ICML-15), pp. 938–947 (2015)
Hua, C., Liu, J.: An improved Slope One recommendation algorithm. Netinfo Secur. 2, 77–81 (2015)
Li, J., Sun, L., Wang, J.: A Slope One collaborative filtering recommendation algorithm using uncertain neighbors optimizing. In: Wang, L., Jiang, J., Lu, J., Hong, L., Liu, B. (eds.) WAIM 2011. LNCS, vol. 7142, pp. 160–166. Springer, Heidelberg (2012). doi:10.1007/978-3-642-28635-3_15
Liu, W.L., Zhang, G.Y., Chen, Z., Zhu, Q.Q.: Collaborative filtering algorithm based on weighted information entropy similarity. J. Zhengzhou Univ. (Eng. Sci.) 33(5), 118–120 (2012)
Schickel-Zuber, V., Faltings, B.: Using hierarchical clustering for learning theontologies used in recommendation systems. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 599–608 (2007)
Li, D., Xin, C., Wang, K.: Evaluation of collaborative filtering algorithm based on different data sets. J. Tsinghua Univ. JCR Sci. Ed. 49(4), 590–594 (2009)
Wang, J., De Vries, A.P., Reinders, M.J.: Unifying user-based and item-based collaborative filtering approaches by similarity fusion. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 501–508 (2006)
Acknowledgments
This work was supported by National Natural Science Foundations of China (No. 61170192).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Tian, S., Ou, L. (2016). An Improved Slope One Algorithm Combining KNN Method Weighted by User Similarity. In: Song, S., Tong, Y. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9998. Springer, Cham. https://doi.org/10.1007/978-3-319-47121-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-47121-1_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47120-4
Online ISBN: 978-3-319-47121-1
eBook Packages: Computer ScienceComputer Science (R0)