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Social Collaborative Filtering by Trust
Recommender systems are used to accurately and actively provide users with potentially interesting information or services. Collaborative filtering is a widely adopted approach to recommendation, but sparse data and cold-start users are often barriers to providing high quality recommendations. To ad...
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Published in: | IEEE transactions on pattern analysis and machine intelligence 2017-08, Vol.39 (8), p.1633-1647 |
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container_title | IEEE transactions on pattern analysis and machine intelligence |
container_volume | 39 |
creator | Yang, Bo Lei, Yu Liu, Jiming Li, Wenjie |
description | Recommender systems are used to accurately and actively provide users with potentially interesting information or services. Collaborative filtering is a widely adopted approach to recommendation, but sparse data and cold-start users are often barriers to providing high quality recommendations. To address such issues, we propose a novel method that works to improve the performance of collaborative filtering recommendations by integrating sparse rating data given by users and sparse social trust network among these same users. This is a model-based method that adopts matrix factorization technique that maps users into low-dimensional latent feature spaces in terms of their trust relationship, and aims to more accurately reflect the users reciprocal influence on the formation of their own opinions and to learn better preferential patterns of users for high-quality recommendations. We use four large-scale datasets to show that the proposed method performs much better, especially for cold start users, than state-of-the-art recommendation algorithms for social collaborative filtering based on trust. |
doi_str_mv | 10.1109/TPAMI.2016.2605085 |
format | article |
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issn | 0162-8828 1939-3539 2160-9292 |
language | eng |
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source | IEEE Xplore (Online service) |
subjects | Acquisitions & mergers Cold starts Collaboration collaborative filtering Computer science Data models Electronic mail Filtration matrix factorization Performance enhancement Predictive models Recommender system Recommender systems Social network services State of the art trust network Writing |
title | Social Collaborative Filtering by Trust |
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