Modeling implicit feedback based on bandit learning for recommendation
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DOI: 10.1016/j.neucom.2021.03.072
Abstract: Abstract Implicit feedback such as clicks and favorites has been widely studied and applied to recommender systems due to its low collection cost and rich hidden information. In this paper, the recommendation based on implicit… read more here.
Keywords: problem; feedback; implicit feedback; model ... See more keywords
Embedding-Augmented Generalized Matrix Factorization for Recommendation with Implicit Feedback
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DOI: 10.1109/mis.2020.3036136
Abstract: Learning effective representations of users and items is crucially important to recommendation with implicit feedback. Matrix factorization is the basic idea to derive the representations of users and items by decomposing the given interaction matrix.… read more here.
Keywords: matrix; generalized matrix; matrix factorization; implicit feedback ... See more keywords
Collaborative List-and-Pairwise Filtering From Implicit Feedback
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DOI: 10.1109/tkde.2020.3016732
Abstract: The implicit feedback based collaborative filtering (CF) has attracted much attention in recent years, mainly because users implicitly express their preferences in many real-world scenarios. The current mainstream pairwise methods optimize the Area Under the… read more here.
Keywords: implicit feedback; inline formula; pairwise; tex math ... See more keywords
Recommending Crowdfunding Project: A Graph Kernel-Based Link Prediction Method for Extremely Sparse Implicit Feedback
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/5126140
Abstract: It is a critical task to provide recommendation on implicit feedback, and one of the biggest challenges is extreme data sparsity. To tackle the problem, a graph kernel-based link prediction method is proposed in this… read more here.
Keywords: link prediction; implicit feedback; feedback; graph kernel ... See more keywords
Neural Matrix Factorization Recommendation for User Preference Prediction Based on Explicit and Implicit Feedback
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/9593957
Abstract: Explicit feedback and implicit feedback are two important types of heterogeneous data for constructing a recommendation system. The combination of the two can effectively improve the performance of the recommendation system. However, most of the… read more here.
Keywords: based explicit; matrix factorization; implicit feedback; explicit implicit ... See more keywords