More IR than IF. The user has to express his information need in a query kind of way wich is mapped as a rough set on the document space. Nothing interesting, except maybe for a set view on my system. Furthermore the documents have to be classified before the algorithm can be applied. A good introduction to rough set theory and how it can be applied for information filtering.
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%0 Journal Article
%1 IF011
%A Li, Y.
%A Zhang, C.
%A Swan, J. R.
%D 2000
%J Knowledge-Based Systems
%K Information agents. filtering, information intelligent rough set,
%P 285-296
%T An Information Filtering Model on the Web and its Application in JobAgent.
%V 13
@article{IF011,
added-at = {2009-06-22T10:05:09.000+0200},
author = {Li, Y. and Zhang, C. and Swan, J. R.},
biburl = {https://www.bibsonomy.org/bibtex/24d4ec125b661bf8fc777438a72e337df/n.nanas},
interhash = {47c0a9247f8dfcb7277e51ac67aa4d9e},
intrahash = {4d4ec125b661bf8fc777438a72e337df},
journal = {Knowledge-Based Systems},
keywords = {Information agents. filtering, information intelligent rough set,},
pages = {285-296},
qnote = {More IR than IF. The user has to express his information need in a query kind of way wich is mapped as a rough set on the document space. Nothing interesting, except maybe for a set view on my system. Furthermore the documents have to be classified before the algorithm can be applied. A good introduction to rough set theory and how it can be applied for information filtering.},
timestamp = {2009-06-23T10:19:15.000+0200},
title = {An Information Filtering Model on the Web and its Application in JobAgent.},
volume = 13,
year = 2000
}
