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Author:Mladenic, D.
Grobelnik, M.
Title:Feature selection on hierarchy of web documents
Journal:Decision Support Systems
2003 : APR, VOL. 35:1, p. 45-88
Index terms:LEARNING
INTERNET
INFORMATION TECHNOLOGY
DOCUMENTATION
Language:eng
Abstract:The paper describes feature subset selection used in learning on text data (text learning) and gives a brief overview of feature subset selection commonly used in machine learning. Several known and some new feature scoring measures appropriate for feature subset selection on large text data are described and related to each other. Experimental comparison of the described measures is given on real-world data collected from the Web. Machine learning techniques are used on data collected from Yahoo, a large text hierarchy of Web documents. Our approach includes some original ideas for handling large number of features, categories and documents.
SCIMA record nr: 250326
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