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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 29 / No.1: The Twenty-Ninth Conference on Artificial Intelligence

TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings

March 8, 2023

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Authors

Guibing Guo

Nanyang Technological University


Jie Zhang

Nanyang Technological University


Neil Yorke-Smith

American University of Beirut and University of Cambridge


DOI:

10.1609/aaai.v29i1.9153


Abstract:

Collaborative filtering suffers from the problems of data sparsity and cold start, which dramatically degrade recommendation performance. To help resolve these issues, we propose TrustSVD, a trust-based matrix factorization technique. By analyzing the social trust data from four real-world data sets, we conclude that not only the explicit but also the implicit influence of both ratings and trust should be taken into consideration in a recommendation model. Hence, we build on top of a state-of-the-art recommendation algorithm SVD++ which inherently involves the explicit and implicit influence of rated items, by further incorporating both the explicit and implicit influence of trusted users on the prediction of items for an active user. To our knowledge, the work reported is the first to extend SVD++ with social trust information. Experimental results on the four data sets demonstrate that our approach TrustSVD achieves better accuracy than other ten counterparts, and can better handle the concerned issues.

Topics: AAAI

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HOW TO CITE:

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings Proceedings of the AAAI Conference on Artificial Intelligence, 29 (2015) .

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings AAAI 2015, .

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith (2015). TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings. Proceedings of the AAAI Conference on Artificial Intelligence, 29, .

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith. TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings. Proceedings of the AAAI Conference on Artificial Intelligence, 29 2015 p..

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith. 2015. TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings. "Proceedings of the AAAI Conference on Artificial Intelligence, 29". .

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith. (2015) "TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings", Proceedings of the AAAI Conference on Artificial Intelligence, 29, p.

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith, "TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings", AAAI, p., 2015.

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith. "TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings". Proceedings of the AAAI Conference on Artificial Intelligence, 29, 2015, p..

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith. "TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings". Proceedings of the AAAI Conference on Artificial Intelligence, 29, (2015): .

Guibing Guo|| Jie Zhang|| Neil Yorke-Smith. TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings. AAAI[Internet]. 2015[cited 2023]; .


ISSN: 2374-3468


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