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Abstract: This paper is organized as follows. Section 2 describes the process of deducing the most important keywords. The keyword deduction method is illustrated in section 3 using a WEBSOM-based archive of the well-known Reuters 21,578 text collection. An assessment of the extracted keywords is presented in section 4. A detailed comparison of our keyword selection technique with the original WEBSOM keyword selection method is presented in Section 5 (Update)
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BibTeX entry: (Update)
@misc{ arnulfo-comparing,
author = "Text Archives Arnulfo",
title = "Comparing Keyword Extraction Techniques For Websom",
url = "citeseer.ist.psu.edu/529964.html" }
Citations (may not include all citations):432 Automatic Text Processing: The Transformation (context) - Salton - 1989
149 An Evaluation of Statistical Approaches to Text Categorizati.. - Yang - 1999
76 A Self-Organizing Semantic Map for Information Retrieval (context) - Lin, Soergel et al. - 1991
55 Self-Organization of a Massive Document Collection - Kohonen - 1999
54 WEBSOM-Self-Organizing Maps of Document Collections - Honkela - 1997
30 Self-Organization of Very Large Document Collections: State .. - Kohonen - 1998
10 Feature weighting for lazy learning algorithms - Aha - 1998
7 Statistical Aspects of the WEBSOM System in Organizing Docum.. - Kaski - 1998
4 Mining Text Archives: Creating Readable Maps to Structure an.. - Rauber, Merkl - 1999
4 SOM-Based Methodology for Building Large Text Archives - Azcarraga, Jr - 2001
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3 Han and G (context) - Sam
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Documents on the same site (http://www.comp.nus.edu.sg/~arnulfo/): More
SOM-based Methodology for Building Large Text Archives - Arnulfo Azcarraga And (2001) (Correct)
Word-Streams for Representing Context in Word Maps - Azcarraga, Gopez, Yap, Jr. (2000) (Correct)
Word-Streams for Representing Context in Word Maps - Azcarraga, Gopez, Yap, Jr. (2000) (Correct)
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