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Slope One is a family of algorithms used for collaborative filtering, introduced in a 2005 paper by Daniel Lemire and Anna Maclachlan.〔Daniel 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.〕 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.〔〔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〕 They have also been used as building blocks to improve other algorithms.〔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〕 They are part of major open-source libraries such as Apache Mahout and Easyrec. ==Item-based collaborative filtering of rated resources and overfitting== When ratings of items are available, such as is the case when people are given the option of ratings resources (between 1 and 5, for example), collaborative filtering aims to predict the ratings of one individual based on his past ratings and on a (large) database of ratings contributed by other users. Example: Can we predict the rating an individual would give to the new Celine Dion album given that he gave the Beatles 5 out of 5? In this context, item-based collaborative filtering 〔Slobodan Vucetic, Zoran Obradovic: Collaborative Filtering Using a Regression-Based Approach. Knowl. Inf. Syst. 7(1): 1-22 (2005)〕〔Badrul M. Sarwar, George Karypis, Joseph A. Konstan, John Riedl: Item-based collaborative filtering recommendation algorithms. WWW 2001: 285-295〕 predicts the ratings on one item based on the ratings on another item, typically using linear regression (). Hence, if there are 1,000 items, there could be up to 1,000,000 linear regressions to be learned, and so, up to 2,000,000 regressors. This approach may suffer from severe overfitting〔 unless we select only the pairs of items for which several users have rated both items. A better alternative may be to learn a simpler predictor such as : experiments show that this simpler predictor (called Slope One) sometimes outperforms〔 linear regression while having half the number of regressors. This simplified approach also reduces storage requirements and latency. Item-based collaborative filtering is just one form of collaborative filtering. Other alternatives include user-based collaborative filtering where relationships between users are of interest, instead. However, item-based collaborative filtering is especially scalable with respect to the number of users. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Slope One」の詳細全文を読む スポンサード リンク
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