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Information Filtering (information + filtering)

Distribution by Scientific Domains

Engineering	80%

Selected Abstracts

Improvement of information filtering by independent components selection

ELECTRICAL ENGINEERING IN JAPAN, Issue 2 2008
Takeru Yokoi
Abstract We propose an improvement of an information filtering process with independent components selection. The independent components are obtained by Independent Components Analysis and considered as topics. Selection of independent components is an efficient method of improving the accuracy of the information filtering for the purpose of extraction of similar topics by focusing on their meanings. To achieve this, we select the topics by Maximum Distance Algorithm with Jensen-Shannon divergence. In addition, document vectors are represented by the selected topics. We create a user profile from transformed data with a relevance feedback. Finally, we sort documents by the user profile and evaluate the accuracy by imputation precision. We carried out an evaluation experiment to confirm the validity of the proposed method considering meanings of components used in this experiment. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(2): 49,56, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20519 [source]

A metagenetic algorithm for information filtering and collection from the World Wide Web

EXPERT SYSTEMS, Issue 2 2001
Z.N. Zacharis
This paper describes the implementation of evolutionary techniques for information filtering and collection from the World Wide Web. We consider the problem of building intelligent agents to facilitate a person's search for information on the Web. An intelligent agent has been developed that uses a metagenetic algorithm in order to collect and recommend Web pages that will be interesting to the user. The user's feedback on the agent's recommendations drives the learning process to adapt the user's profile with his/her interests. The software agent utilizes the metagenetic algorithm to explore the search space of user interests. Experimental results are presented in order to demonstrate the suitability of the metagenetic algorithm's approach on the Web. [source]

A decision theoretic approach to combining information filters: An analytical and empirical evaluation

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 3 2006
Yuval Elovici
The outputs of several information filtering (IF) systems can be combined to improve filtering performance. In this article the authors propose and explore a framework based on the so-called information structure (IS) model, which is frequently used in Information Economics, for combining the output of multiple IF systems according to each user's preferences (profile). The combination seeks to maximize the expected payoff to that user. The authors show analytically that the proposed framework increases users expected payoff from the combined filtering output for any user preferences. An experiment using the TREC-6 test collection confirms the theoretical findings. [source]