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Combining activity-evaluation information with NMF for trust-link prediction in social media
conference contribution
posted on 2023-05-23, 11:14 authored by Matsutani, K, Kumano, M, Kimura, M, Saito, K, Ohara, K, Motoda, HAcquiring a network of trust relations among users in social media sites, e.g., item-review sites, is important for analyzing users' behavior and efficiently finding reliable information on the Web. We address the problem of predicting trustlinks among users for an item-review site. Non-negative matrix factorization (NMF) methods have recently been shown useful for trust-link prediction in such a site where both link and activity information is available. Here, a user activity in an item-review site means posting a review and giving a rating for an item. In this paper, for better trust-link prediction, we propose a new NMF method that incorporates people's evaluation of users' activities as well as trust-links and users' activities themselves. We further apply it to an analysis of users' behavior. Using two real world item-review sites, we experimentally demonstrate the effectiveness of the proposed method.
History
Publication title
Proceedings of the 2015 IEEE International Conference on Big DataEditors
H Ho, BC Ooi, MJ Zaki, X Hu, L Haas, V Kumar, S Rachuri, S Yu, M Hui-Hsiao, J Li, F Luo, S Pyne, K OPagination
2263-2272ISBN
9781479999255Department/School
School of EngineeringPublisher
IEEE-Inst Electrical Electronics Engineers IncPlace of publication
United States of AmericaEvent title
2015 IEEE International Conference on Big DataEvent Venue
Santa Clara, CA, USADate of Event (Start Date)
2015-10-29Date of Event (End Date)
2015-11-01Rights statement
Copyright 2015 IEEERepository Status
- Restricted