%0 Conference Paper %1 li2012social %A Li, Xin %A Su, Xin %A Wang, Mengyue %B Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries %C New York, NY, USA %D 2012 %I ACM %K analysis kernel network recommender sna %P 409--410 %R 10.1145/2232817.2232915 %T Social network-based recommendation: a graph random walk kernel approach %U http://doi.acm.org/10.1145/2232817.2232915 %X 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. %@ 978-1-4503-1154-0

@inproceedings{li2012social, 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.}, acmid = {2232915}, added-at = {2012-08-31T17:26:43.000+0200}, address = {New York, NY, USA}, author = {Li, Xin and Su, Xin and Wang, Mengyue}, biburl = {https://www.bibsonomy.org/bibtex/289c61b6140962b5b870f5fa34a615678/folke}, booktitle = {Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries}, description = {Social network-based recommendation}, doi = {10.1145/2232817.2232915}, interhash = {5c3f0360ac3718b92ab3de4f53a0dd65}, intrahash = {89c61b6140962b5b870f5fa34a615678}, isbn = {978-1-4503-1154-0}, keywords = {analysis kernel network recommender sna}, location = {Washington, DC, USA}, numpages = {2}, pages = {409--410}, publisher = {ACM}, series = {JCDL '12}, timestamp = {2012-09-03T11:59:47.000+0200}, title = {Social network-based recommendation: a graph random walk kernel approach}, url = {http://doi.acm.org/10.1145/2232817.2232915}, year = 2012 }