Utilizing Physical and Social Context to Improve Recommender Systems Export

@inproceedings{Woerndl_WI-IATW_2007, abstract = {Context has rarely been incorporated into recommender systems so far, but physical (e.g. a user's location) or social (e.g. the social network of a user)context can be useful sources for improving recommender systems. In this paper, we first discuss some principles for context-awareness in recommender systems. Then we present our hybrid recommender system for recommending applications to users of mobile devices. Finally, we describe our approach to utilize social networks to enhance collaborative filtering. Our evaluation shows that the social recommender outperforms traditional collaborative filtering algorithms in our scenario.}, address = {Washington, DC, USA}, author = {Woerndl, Wolfgang and Groh, Georg}, booktitle = {WI-IATW '07: Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops}, citeulike-article-id = {6075111}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1339674}, isbn = {0-7695-3028-1}, keywords = {context, mobile\_devices, recommender-systems, social}, pages = {123--128}, posted-at = {2009-11-06 21:22:36}, priority = {2}, publisher = {IEEE Computer Society}, title = {Utilizing Physical and Social Context to Improve Recommender Systems}, url = {http://portal.acm.org/citation.cfm?id=1339674}, year = {2007} }

TY - CONF ID - Woerndl_WI-IATW_2007 L3 - citeulike-article-id:6075111 N2 - Context has rarely been incorporated into recommender systems so far, but physical (e.g. a user's location) or social (e.g. the social network of a user)context can be useful sources for improving recommender systems. In this paper, we first discuss some principles for context-awareness in recommender systems. Then we present our hybrid recommender system for recommending applications to users of mobile devices. Finally, we describe our approach to utilize social networks to enhance collaborative filtering. Our evaluation shows that the social recommender outperforms traditional collaborative filtering algorithms in our scenario. SN - 0-7695-3028-1 AD - Washington, DC, USA EP - 128 TI - Utilizing Physical and Social Context to Improve Recommender Systems PB - IEEE Computer Society T2 - WI-IATW '07: Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops SP - 123 KW - context KW - mobile_devices KW - recommender-systems KW - social AU - Woerndl, Wolfgang AU - Groh, Georg PY - 2007/// UR - http://portal.acm.org/citation.cfm?id=1339674 ER -