Slope One is a family of algorithms used for collaborative filtering, introduced in a 2005 paper by Daniel Lemire and Anna Maclachlan.[1] Arguably, it is the simplest form of non-trivial item-based collaborative filtering based on ratings. Their simplicity makes it especially easy to implement them efficiently while their accuracy is often on par with more complicated and computationally expensive algorithms.[1][2] They have also been used as building blocks to improve other algorithms.[3][4][5][6][7][8][9] They are part of major open-source libraries such as Apache Mahout and Easyrec.
^ abDaniel Lemire, Anna Maclachlan, Slope One Predictors for Online Rating-Based Collaborative Filtering, In SIAM Data Mining (SDM'05), Newport Beach, California, April 21–23, 2005.
^Fidel Cacheda, Victor Carneiro, Diego Fernandez, and Vreixo Formoso. 2011. Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems. ACM Trans. Web 5, 1, Article 2
^Pu Wang, HongWu Ye, A Personalized Recommendation Algorithm Combining Slope One Scheme and User Based Collaborative Filtering, IIS '09, 2009.
^DeJia Zhang, An Item-based Collaborative Filtering Recommendation Algorithm Using Slope One Scheme Smoothing, ISECS '09, 2009.
^Min Gaoa, Zhongfu Wub, and Feng Jiang, Userrank for item-based collaborative filtering recommendation, Information Processing Letters Volume 111, Issue 9, 1 April 2011, pp. 440-446.
^Mi, Zhenzhen and Xu, Congfu, A Recommendation Algorithm Combining Clustering Method and Slope One Scheme, Lecture Notes in Computer Science 6840, 2012, pp. 160-167.
^Danilo Menezes, Anisio Lacerda, Leila Silva, Adriano Veloso, and Nivio Ziviani. 2013. Weighted slope one predictors revisited. In Proceedings of the 22nd international conference on World Wide Web companion (WWW '13 Companion). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 967-972.
^Sun, Z., Luo, N., Kuang, W., One real-time personalized recommendation systems based on Slope One algorithm, FSKD 2011, 3, art. no. 6019830, 2012 pp. 1826-1830.
^Gao, M., Wu, Z., Personalized context-aware collaborative filtering based on neural network and slope one, LNCS 5738, 2009, pp. 109-116
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