A Hybrid Recommender System for Sequential Recommendation: Combining Similarity Models With Markov Chains

With the growth of artificial intelligence technology, the importance of recommender systems that recommend personalized content has increased. The general form of the recommender system usually analyzes the users' log information to provide them with contents that they are interested in. Howev...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.190136-190146
Hauptverfasser:	Yang, Yeongwook, Jang, Hong-Jun, Kim, Byoungwook
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Biological system modeling Computational modeling content-based filtering Customization Data models hybrid recommendation Hybrid systems Item similarity model Markov analysis Markov chains Markov processes Motion pictures Recommender systems sequential recommendation Similarity Sparsity
Online-Zugang:	Volltext
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