Intelligent information-sharing systems
Communications of the ACM
Choices: an introduction to decision theory
Choices: an introduction to decision theory
I3R: a new approach to the design of document retrieval systems
Journal of the American Society for Information Science
Communications of the ACM - Special issue on information filtering
Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Personalized information delivery: an analysis of information filtering methods
Communications of the ACM - Special issue on information filtering
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Measuring retrieval effectiveness based on user preference of documents
Journal of the American Society for Information Science
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
Communications of the ACM
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Helping people find what they don't know
Communications of the ACM
Collaborative filtering and the generalized vector space model (poster session)
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Technical paper recommendation: a study in combining multiple information sources
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
A graph model for E-commerce recommender systems
Journal of the American Society for Information Science and Technology
Evaluating implicit feedback models using searcher simulations
ACM Transactions on Information Systems (TOIS)
Journal of the American Society for Information Science and Technology
Collaborative use of individual search histories
Interacting with Computers
Philosophy and information studies
Annual Review of Information Science and Technology
Exploring evaluation criteria of social navigational tools on social media: a case study of aNobii
Proceedings of the 4th Information Interaction in Context Symposium
Journal of the American Society for Information Science and Technology
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The core of any document retrieval system is a mechanism that ranks the documents in a large collection in order of the likelihood with which they match the preferences of any person who interacts with the system. Given a broader interpretation of recommending than is commonly accepted, such a preference ordering may be viewed as a recommendation, made by the system to the information seeker, that is itself typically derived through synthesis of multiple preference orderings expressed as recommendations by indexers, information seekers, and document authors. The ERIn (Evaluation-Recommendation-Information) model, a decision-theoretic framework for understanding information-related activity, highlights the centrality of recommending in the document retrieval process, and may be used to clarify the respects in which indexing, rating, and citation may be considered analogous, as well as to make explicit the points at which content-based, collaboration-based, and context-based flavors of document retrieval systems vary.