Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Learning personal preferences on online newspaper articles from user behaviors
Selected papers from the sixth international conference on World Wide Web
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
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
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
Personalised hypermedia presentation techniques for improving online customer relationships
The Knowledge Engineering Review
IEEE Transactions on Knowledge and Data Engineering
A time-based approach to effective recommender systems using implicit feedback
Expert Systems with Applications: An International Journal
I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Rate it again: increasing recommendation accuracy by user re-rating
Proceedings of the third ACM conference on Recommender systems
Characterisation of explicit feedback in an online music recommendation service
Proceedings of the fourth ACM conference on Recommender systems
Comparison of implicit and explicit feedback from an online music recommendation service
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
User Modeling by CLC and Feedback Behavior
BCGIN '11 Proceedings of the 2011 International Conference on Business Computing and Global Informatization
An efficient web recommendation system based on modified IncSpan algorithm
International Journal of Knowledge and Web Intelligence
Hierarchical browsing and search of large image databases
IEEE Transactions on Image Processing
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The knowledge base of a traditional web recommender system is constructed from web logs, reflecting past user preferences which may change over time. In this paper, an algorithm, based on implicit user feedback on top N recommendations and normalised mutual information, is proposed for collaborative personalised web recommender system. The proposed algorithm updates the knowledge base taking into account the changing user preferences, in order to generate better recommendations in future. The proposed approach and collaborative personalised web recommender systems without feedback are compared. Significant improvements are observed in precision, recall and F1 measure for proposed approach.