Abstract
Collaborative filtering (CF) framework in recommendation is a very popular technique for providing personalized recommendation. Slope one predictor is a model-based CF which has received good attention from researchers and practitioners. In this paper, we revisit the slope one predictor to incorporate strong features of neighbourhood-based CF into it for providing personalized recommendation to users. Preliminary results with two real-world datasets are very promising. Proposed technique outperforms original slope one and its performance is at par with a variant of slope one introduced recently.
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Shaw, R., Patra, B.K. (2021). Slope One Meets Neighbourhood: Revisiting Slope One Predictor in Collaborative Filtering. In: Giri, D., Buyya, R., Ponnusamy, S., De, D., Adamatzky, A., Abawajy, J.H. (eds) Proceedings of the Sixth International Conference on Mathematics and Computing. Advances in Intelligent Systems and Computing, vol 1262. Springer, Singapore. https://doi.org/10.1007/978-981-15-8061-1_18
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DOI: https://doi.org/10.1007/978-981-15-8061-1_18
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