@inproceedings{f1340877e7d8453cbc050f590af1827a,
title = "Social network-based recommendation: A graph random walk kernel approach",
abstract = "Traditional recommender system research often explores customer, product, and transaction information in providing recommendations. Social relationships in social networks are related to individuals' preferences. This study investigates the product recommendation problem based solely on people's social network information. Taking a kernel-based approach, we capture consumer social influence similarities into a graph random walk kernel and build SVR models to predict consumer opinions. In experiments on a dataset from a movie review website, our proposed model outperforms trust-based models and state-of-the-art graph kernels.",
keywords = "graph kernel, random walk, recommendation, social network",
author = "Xin Li and Xin Su and Mengyue Wang",
year = "2012",
doi = "10.1145/2232817.2232915",
language = "English",
isbn = "9781450311540",
series = "Proceedings of the ACM/IEEE Joint Conference on Digital Libraries",
pages = "409--410",
booktitle = "JCDL '12 - Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries",
note = "12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12 ; Conference date: 10-06-2012 Through 14-06-2012",
}