Relevance Filtering

Paul E. Baclace. Explores a hybrid learning algorithm applied to the problem of Information Intake Filtering (IIF). Information Intake refers to information that impinges upon users.

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2. Minimizing Information Overload: The Ranking of Electronic Messages

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Personal Information Intake Filtering Presented at the Bellcore Information Filtering Workshop, This project was paid for by Autodesk, Translated to HTML from Framemaker, This article explores a hybrid learning algorithm applied to the problem of Information Intake Filtering (IIF). Information
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The decision to examine a message at a particular point in time should be made rationally and economically if the message recipient is to operate efficiently. Our model provides a formal method for minimizing expected information overload through information filtering.

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Minimizing Information Overload: the Ranking of Electronic Messages, Journal of Information Science, 15, 1989, p. 179-189. The decision to examine a message at a particular point in time should be made rationally and economically if the message recipient is to operate efficiently. Electronic
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3. Collaborative Filtering Research Papers

User-updated directory of collaborative filtering research papers with abstracts, links to the full papers, and reader comments.

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Internet Business Consultant Call Toll Free: 1 (800) 409-2501 Collaborative Filtering Research Papers Summary : 64 abstracts with links to the full papers and reader comments. ( 2005 ), by Manos Papagelis, Dimitris Plexousakis (University of Crete & FORTH-ICS, Greece) Recommendation agents
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4. The Mole

Software analyzes the context in which words and sentences are used and dynamically links their relationships. Features purchasing and contact information.

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5. StumbleUpon

Free web-browser extension which acts as an intelligent browsing tool for discovering and sharing web sites; recommendation engine is based on explicit interests survey and feedback via site ratings. Features screen shots, toolbar guide and contact information.

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6. Augmenting Information Seeking on the World Wide Web Using Collaborative Filtering Techniques

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StumbleUpon discovers web sites based on your interests, learns what you like and brings you more.
for recommendations. New member? . StumbleUpon helps you discover the best of the web. Recommended Sites from 7,960,784 members about how StumbleUpon helps you discover the best sites on the web. Get our weekly newsletter to © StumbleUpon 2001-2009 Join to discover 7,960,784 people's

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Applying Bibliometric analysis, filtering techniques, and collaborative technologies to Web usage data that can, in turn leverage a Web user's Information Seeking behavior.

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