Factorization-based primary dimension modelling for multidimensional data in recommender systems

In recent years, multidimensional data is becoming increasingly popular in recommender systems. For example, social tagging systems encourage users to employ user-defined keywords to help manage content in a personalized way. Recommender systems built upon social tagging systems utilize social taggi...

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Veröffentlicht in:	International journal of machine learning and cybernetics Jg. 10; H. 8; S. 2209 - 2228
Hauptverfasser:	Tang, Xiaoyu, Xu, Yue, Geva, Shlomo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2019 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial Intelligence Collaboration Complex Systems Computational Intelligence Context Control Customization Data analysis Eigenvectors Engineering Factorization Filtration Mechatronics Methods Multidimensional data Multidimensional methods Neighborhoods Original Article Pattern Recognition Recommender systems Robotics Systems Biology Tagging Tags Tensors User behavior User profiles Multidimensional data Social tagging data Collaborative filtering Tensor factorization Recommender systems User profiling
ISSN:	1868-8071, 1868-808X
Online-Zugang:	Volltext
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