Computer
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Automatic personalization based on Web usage mining
Communications of the ACM
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
RecTree: An Efficient Collaborative Filtering Method
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Relational Markov models and their application to adaptive web navigation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
ACM Transactions on Information Systems (TOIS)
Integrating AHP and data mining for product recommendation based on customer lifetime value
Information and Management
IEEE Transactions on Knowledge and Data Engineering
Scalable collaborative filtering using cluster-based smoothing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
WordNet-based User Profiles for Neighborhood Formation in Hybrid Recommender Systems
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
A new approach for combining content-based and collaborative filters
Journal of Intelligent Information Systems
A collaborative filtering framework based on fuzzy association rules and multiple-level similarity
Knowledge and Information Systems
Collaborative Filtering for Multi-class Data Using Belief Nets Algorithms
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Guest Editors' Introduction: Recommender Systems
IEEE Intelligent Systems
Similarity Measure and Instance Selection for Collaborative Filtering
International Journal of Electronic Commerce
ACM Transactions on Information Systems (TOIS)
A new restoration-based recommender system for shopping buddy smart carts
International Journal of Business Information Systems
Expert Systems with Applications: An International Journal
Cross-representation mediation of user models
User Modeling and User-Adapted Interaction
Feature-based recommendations for one-to-one marketing
Expert Systems with Applications: An International Journal
Content-based recommendation systems
The adaptive web
Unified collaborative filtering model based on combination of latent features
Expert Systems with Applications: An International Journal
Extending the Bayesian Classifier to a Context-Aware Recommender System for Mobile Devices
ICIW '10 Proceedings of the 2010 Fifth International Conference on Internet and Web Applications and Services
Expert Systems with Applications: An International Journal
Collaborative error-reflected models for cold-start recommender systems
Decision Support Systems
A study on collaborative recommender system using fuzzy-multicriteria approaches
International Journal of Business Information Systems
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Adoption of business intelligence systems in Indian fashion retail
International Journal of Business Information Systems
Market basket analysis a data mining application in Indian retailing
International Journal of Business Information Systems
Collaborative user modeling for enhanced content filtering in recommender systems
Decision Support Systems
Input online review data and related bias in recommender systems
Decision Support Systems
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Recommender system technology can assist customers of a company to choose an appropriate product or service after learning their preferences. But this technology suffers from some problems such as scalability and sparsity. Since users express their opinions implicitly based on some specific attributes of items, this paper proposes a collaborative filtering algorithm based on attributes of items to address these problems. Attributes weight vector for each user is considered as a chromosome in genetic algorithm. This algorithm optimises the weights according to historical rating. A weighted C-means algorithm also is introduced to cluster users based on the optimised attributes weight vector. Finally, recommendation is generated by a user based similarity in each cluster. The experimental results show that our proposed method outperforms current algorithms and can perform superiorly and alleviates problems such as sparsity and precision quality. The main contribution of this paper is addressing sparsity problem using attribute weighting and scalability problem using weighted C-means algorithm.