Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
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
A hybrid user model for news story classification
UM '99 Proceedings of the seventh international conference on User modeling
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Data Mining and Knowledge Discovery
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
A graph model for E-commerce recommender systems
Journal of the American Society for Information Science and Technology
Proceedings of the 10th international conference on Intelligent user interfaces
Integrating AHP and data mining for product recommendation based on customer lifetime value
Information and Management
Similarity Measure and Instance Selection for Collaborative Filtering
International Journal of Electronic Commerce
Detection of the customer time-variant pattern for improving recommender systems
Expert Systems with Applications: An International Journal
Mining changes in customer buying behavior for collaborative recommendations
Expert Systems with Applications: An International Journal
On-line personalized sales promotion in electronic commerce
Expert Systems with Applications: An International Journal
Feature-based recommendations for one-to-one marketing
Expert Systems with Applications: An International Journal
Proceedings of the 2008 Euro American Conference on Telematics and Information Systems
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Information Sciences: an International Journal
Web user browse behavior characteristic analysis based on a BC tree
AMT'10 Proceedings of the 6th international conference on Active media technology
Information Systems Frontiers
Effective hybrid recommendation combining users-searches correlations using tensors
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Personalized book recommendations created by using social media data
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Expert Systems with Applications: An International Journal
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Personalized implicit learning in a music recommender system
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Predicting the ratings of multimedia items for making personalized recommendations
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Electronic Commerce Research and Applications
A personalized trustworthy seller recommendation in an open market
Expert Systems with Applications: An International Journal
What to read next?: making personalized book recommendations for K-12 users
Proceedings of the 7th ACM conference on Recommender systems
Exploiting two-faceted web of trust for enhanced-quality recommendations
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
The development of efficient customer profile models is crucial for improving the recommendation quality of the recommendation system. In this paper, we propose a new customer profile model based on individual and group behavior information such as clicks, basket insertions, purchases, and interest fields. We also implement a recommendation system using the proposed model, and evaluate the recommendation performance of the proposed model in terms of several well known evaluation metrics. Experimental results show that the proposed model has a better recommendation performance than existing models.