Document (#25317)

Author

Dolin, R.
Agrawal, D.
El Abbadi, A.
Pearlman, J.

Title

Using automated classification for summarizing and selecting heterogeneous information sources

Source

D-Lib magazine. 4(1998) no.1

Year

1998

Pages

11 S.

Abstract

Information retrieval over the Internet increasingly requires the filtering of thousands of heterogeneous information sources. Important sources of information include not only traditional databases with structured data and queries, but also increasing numbers of non-traditional, semi- or unstructured collections such as Web sites, FTP archives, etc. As the number and variability of sources increases, new ways of automatically summarizing, discovering, and selecting collections relevant to a user's query are needed. One such method involves the use of classification schemes, such as the Library of Congress Classification (LCC) [10], within which a collection may be represented based on its content, irrespective of the structure of the actual data or documents. For such a system to be useful in a large-scale distributed environment, it must be easy to use for both collection managers and users. As a result, it must be possible to classify documents automatically within a classification scheme. Furthermore, there must be a straightforward and intuitive interface with which the user may use the scheme to assist in information retrieval (IR).

Footnote

Vgl. auch: http://www.dlib.org/dlib/january98/dolin/01dolin.html

Theme

Automatisches Klassifizieren

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4. Hochheiser, H.; Shneiderman, B.: Understanding patterns of user visits to Web sites : Interactive Starfield visualizations of WWW log data (1999) 0.16

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5. Xu, J.; Croft, W.B.: Topic-based language models for distributed retrieval (2000) 0.16

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