Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
MusicFX: an arbiter of group preferences for computer supported collaborative workouts
CSCW '98 Proceedings of the 1998 ACM conference on Computer supported cooperative work
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Flytrap: intelligent group music recommendation
Proceedings of the 7th international conference on Intelligent user interfaces
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Sparsity, scalability, and distribution in recommender systems
Sparsity, scalability, and distribution in recommender systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Talk to me: foundations for successful individual-group interactions in online communities
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
TV Program Recommendation for Multiple Viewers Based on user Profile Merging
User Modeling and User-Adapted Interaction
PolyLens: a recommender system for groups of users
ECSCW'01 Proceedings of the seventh conference on European Conference on Computer Supported Cooperative Work
Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective
Information Systems Research
Tailoring recommendations to groups of users: a graph walk-based approach
Proceedings of the 2013 international conference on Intelligent user interfaces
Recommendation in Online Health Communities
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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We propose a recommendation procedure for online book communities called ''Commenders.'' Its purpose is to enhance the effectiveness of community recommendation and also the satisfaction of individual members. The basic idea of our proposed approach is collaborative filtering (CF). It adapts a content-based (CB) filtering algorithm by representing items with keyword features. The proposed recommendation procedure consists of two steps. During the first step, Commenders finds neighbors using community preferences for books and their feature information, and then it generates a CF-based recommendation list. The second step removes irrelevant books from the CF-based list using the keyword preferences of individual members. Commenders is designed to reduce individual member dissatisfaction with the process of finding desired books within an online community. To evaluate the procedure, we built a prototype system and performed experiments. Our experimental results show that the proposed system offers higher quality recommendations than the traditional collaborative filtering system. The proposed system has consistently higher precision, and individual members are more satisfied using this system.