Document (#28558)

Author
Mukhopadhyay, S.
Peng, S.
Raje, R.
Mostafa, J.
Palakal, M.
Title
Distributed multi-agent information filtering : a comparative study
Source
Journal of the American Society for Information Science and Technology. 56(2005) no.8, S.834-842
Year
2005
Abstract
Information filtering is a technique to identify, in large collections, information that is relevant according to some criteria (e.g., a user's personal interests, or a research project objective). As such, it is a key technology for providing efficient user services in any large-scale information infrastructure, e.g., digital libraries. To provide large-scale Information filtering services, both computational and knowledge management issues need to be addressed. A centralized (single-agent) approach to information filtering suffers from serious drawbacks in terms of speed, accuracy, and economic considerations, and becomes unrealistic even for medium-scale applications. In this article, we discuss two distributed (multiagent) information filtering approaches, that are distributed with respect to knowledge or functionality, to overcome the limitations of single-agent centralized information filtering. Large-scale experimental studies involving the weIl-known TREC data set are also presented to illustrate the advantages of distributed filtering as weIl as to compare the different distributed approaches.

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