Extended matrix factorization with entity network construction for recommendation
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-021-03345-z
Abstract: In order to improve the performance of recommender systems, user social information and item attribute information should be integrated when building the prediction model, which is a hotspot and difficulty in the field of recommender… read more here.
Keywords: users items; recommendation; network; extended matrix ... See more keywords
An Approach to Semantic-Aware Heterogeneous Network Embedding for Recommender Systems.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3233819
Abstract: Recent studies on heterogeneous information network (HIN) embedding-based recommendations have encountered challenges. These challenges are related to the data heterogeneity of the associated unstructured attribute or content (e.g., text-based summary/description) of users and items in… read more here.
Keywords: network; recommendation; users items; hin ... See more keywords
Kernelized Deep Learning for Matrix Factorization Recommendation System Using Explicit and Implicit Information.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3182942
Abstract: In the current matrix factorization recommendation approaches, the item and the user latent factor vectors are with the same dimension. Thus, the linear dot product is used as the interactive function between the user and… read more here.
Keywords: recommendation; users items; factorization recommendation; matrix factorization ... See more keywords
Predicting Dynamic User-Item Interaction with Meta-Path Guided Recursive RNN
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DOI: 10.3390/a15030080
Abstract: Accurately predicting user–item interactions is critically important in many real applications, including recommender systems and user behavior analysis in social networks. One major drawback of existing studies is that they generally directly analyze the sparse… read more here.
Keywords: user item; users items; item; recursive rnn ... See more keywords