Title :
Utilizing Physical and Social Context to Improve Recommender Systems
Author :
Woerndl, Wolfgang ; Groh, Georg
Author_Institution :
Tech. Univ. Muenchen, Muenchen
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.
Keywords :
information filters; ubiquitous computing; collaborative filtering; context awareness; mobile devices; physical context; recommender systems; social context; social networks; social recommender; Collaboration; Conferences; Context modeling; Data models; Filtering algorithms; Information retrieval; Intelligent agent; Intelligent networks; Recommender systems; Social network services; contextrecommender systemscollaborative filteringsocial recommendercontext-aware applications;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology Workshops, 2007 IEEE/WIC/ACM International Conferences on
Conference_Location :
Silicon Valley, CA
Print_ISBN :
0-7695-3028-1
DOI :
10.1109/WI-IATW.2007.123