User Modeling for Recommendation in Blogspace

Authors:
Kangmiao Liu;Wei Chen;Jiajun Bu;Chun Chen;Lijun Zhang
Affiliations:
-;-;-;-;-
Venue:
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Year:
2007

Citing 5
Cited 4

Learning user interest dynamics with a three-descriptor representation

Journal of the American Society for Information Science and Technology
Hybrid Recommender Systems: Survey and Experiments

User Modeling and User-Adapted Interaction
A probabilistic approach to spatiotemporal theme pattern mining on weblogs

Proceedings of the 15th international conference on World Wide Web
E-commerce recommenders' authority: applying the user's opinion relevance in recommender systems

WebMedia '06 Proceedings of the 12th Brazilian Symposium on Multimedia and the web
Exploring in the weblog space by detecting informative and affective articles

Proceedings of the 16th international conference on World Wide Web

Personalized Popular Blog Recommender Service for Mobile Applications

EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Personalized recommendation of popular blog articles for mobile applications

Information Sciences: an International Journal
Compass to locate the user model i need: building the bridge between researchers and practitioners in user modeling

UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Combining reputation and content-based filtering for blog article recommendation in social bookmarking websites

Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business

Quantified Score

Hi-index	0.00

Visualization

Abstract

Weblogs (also known as blogs) have become a key tool not only for individuals to publish posts, but also for obtaining useful information on a daily basis. Compared with traditional Internet services, there is much more personalized information in blogspace. And it is an ideal place to provide personalized services such as recommendation. This paper proposes a novel scheme to model users' interests for recommendation in blogspace. It separates users' interests into long-term and short-term, and models them by integrating their preference categories reflected in individual blog post in a period of time. Interests attenuation algorithm is further introduced to model the decline of users' interests in a specific category. Experimental results show that the proposed scheme can well describe users' interests evolvement.