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Deep Item-based Collaborative Filtering for Top-N Recommendation

Computer Science

Deep Item-based Collaborative Filtering for Top-N Recommendation

F. Xue, X. He, et al.

This research, conducted by Feng Xue, Xiangnan He, Xiang Wang, Jiandong Xu, Kai Liu, and Richang Hong, introduces DeepICF — a neural item-based collaborative filtering that models nonlinear and higher-order item relationships beyond pairwise interactions, and shows on MovieLens and Pinterest that higher-order modeling and an attention-augmented variant (DeepICF+a) improve recommendation performance.... show more
Citation Metrics
Citations
335
Influential Citations
16
Reference Count
48
Citation by Year

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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