An analytic approach to separate users by introducing new combinations of initial centers of clustering
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DOI: 10.1016/j.physa.2020.124185
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References listed on IDEAS
- Maihami, Vafa & Zandi, Danesh & Naderi, Kasra, 2019. "Proposing a novel method for improving the performance of collaborative filtering systems regarding the priority of similar users," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
- Honey Jindal & Shalini Agarwal & Neetu Sardana, 2018. "PowKMeans: A Hybrid Approach for Gray Sheep Users Detection and Their Recommendations," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 13(2), pages 56-69, April.
- Ramezani, Mohsen & Moradi, Parham & Akhlaghian, Fardin, 2014. "A pattern mining approach to enhance the accuracy of collaborative filtering in sparse data domains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 72-84.
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Cited by:
- Rahim Rashidi & Keyhan Khamforoosh & Amir Sheikhahmadi, 2022. "Proposing improved meta-heuristic algorithms for clustering and separating users in the recommender systems," Electronic Commerce Research, Springer, vol. 22(2), pages 623-648, June.
- Li, Yanbin & Zhao, Ke & Zhang, Feng, 2023. "Identification of key influencing factors to Chinese coal power enterprises transition in the context of carbon neutrality: A modified fuzzy DEMATEL approach," Energy, Elsevier, vol. 263(PA).
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Keywords
Collaborative filtering; Gray sheep users; Power item; Power weight; MKMeans++;All these keywords.
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