Leveraging Image Visual Features in Content-Based Recommender System
Joint Authors
Qin, Zhiguang
Qin, Zhen
Deng, Fuhu
Ren, Panlong
Huang, Gu
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-12
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Content-based (CB) and collaborative filtering (CF) recommendation algorithms are widely used in modern e-commerce recommender systems (RSs) to improve user experience of personalized services.
Item content features and user-item rating data are primarily used to train the recommendation model.
However, sparse data would lead such systems unreliable.
To solve the data sparsity problem, we consider that more latent information would be imported to catch users’ potential preferences.
Therefore, hybrid features which include all kinds of item features are used to excavate users’ interests.
In particular, we find that the image visual features can catch more potential preferences of users.
In this paper, we leverage the combination of user-item rating data and item hybrid features to propose a novel CB recommendation model, which is suitable for rating-based recommender scenarios.
The experimental results show that the proposed model has better recommendation performance in sparse data scenarios than conventional approaches.
Besides, training offline and recommendation online make the model has higher efficiency on large datasets.
American Psychological Association (APA)
Deng, Fuhu& Ren, Panlong& Qin, Zhen& Huang, Gu& Qin, Zhiguang. 2018. Leveraging Image Visual Features in Content-Based Recommender System. Scientific Programming،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1214718
Modern Language Association (MLA)
Deng, Fuhu…[et al.]. Leveraging Image Visual Features in Content-Based Recommender System. Scientific Programming No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1214718
American Medical Association (AMA)
Deng, Fuhu& Ren, Panlong& Qin, Zhen& Huang, Gu& Qin, Zhiguang. Leveraging Image Visual Features in Content-Based Recommender System. Scientific Programming. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1214718
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214718