Improving the item to item algorithm of collaborative filtration method for the development of recommendation systems based on the cosine measure by relevant assessment
DOI:
https://doi.org/10.15587/2313-8416.2018.120886Keywords:
correlation, cosine, collaborative, filtration. vector, Tanimoto, user, ID, URLAbstract
The analysis of comparative results of reference systems on the basis of the Tanimoto correlation coefficient in comparison with the "item to item" algorithm of collaborative filtration with the help of relevant assessment is presented. Data for surveys in the form of users with unique IDs are formed. Algorithm of collaborative filtration is based on a cosine measure, which represents the similarity of objects as a cosine between the vectors of purchases in the matrix of users and objects
References
Recommendation system (2016). Wikipedia. Available at: https://uk.wikipedia.org/wiki/Рекомендаційна_система
Collaborative filtration (2012). Habrahabr. Available at: https://habrahabr.ru/post/150399/
Slope One (2015). Available at: https://en.wikipedia.org/wiki/Slope_One
Su, X., Khoshgoftaar, T. M. (2009). A Survey of Collaborative Filtering Techniques. Advances in Artificial Intelligence, 2009, 1–19. doi: 10.1155/2009/421425
Gomzin, A. G., Korshunov, A. V. (2012). Systems of recommendations: an overview of modern approaches. Proceedings of the ISP RAS, 402–417. Available at: http://cyberleninka.ru/article/n/sistemy-rekomendatsiy-obzorsovremennyh-podhodov
Ghazanfar, M. A., Prugel-Bennett, A. (2010). Building Switching Hybrid Recommender System Using Machine Learning Classifiers and Collaborative Filtering. International Journal of Computer Science, 37 (3). Available at: http://www.iaeng.org/IJCS/issues_v37/issue_3/IJCS_37_3_09.pdf
Example ad (2017). Automoto. Available at: https://automoto.ua/uk/Mercedes-Benz-GLE-Class-2017-Khmelnytskyi-18044982.html
Linden, G., Smith, B., York, J. (2003). Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Computing, 7 (1), 76–80. doi: 10.1109/mic.2003.1167344
Hu, Y., Koren, Y., Volinsky, C. (2008). Collaborative filtering for implicit feedback datasets. 2008 Eighth IEEE International Conference on Data Mining. Pisa, 263–272. doi: 10.1109/icdm.2008.22
Sarwar, B. M., Karypis, G., Konstan, J. A. (2001). Item-based collaborative filtering recommendation algorithms. Proceedings of ACM WWW '01. Hong Kong, 285–295. doi: 10.1145/371920.372071
Karypis, G. (2001). Evaluation of object-based top-N algorithms. Proceedings of the tenth international conference on Information and knowledge management – CIKM'01. Atlanta, 247–254. doi: 10.1145/502624.502627
Glushko, M. V., Kucheruk, V. Yu., Mitkovsky, O. (2017). Improvement of the algorithm item to item method of collaborative filtration for the development of advisory systems by the assessment of relevance. Measurement, control and diagnostics in technical systems. Vinnitsa, 215. Available at: http://mpa.vntu.edu.ua/images/conference/conf2017/VCDTS%202017.pdf
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Copyright (c) 2018 Vladimir Kucheruk, Mikhail Hlushko
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