Text Categorization Based on Weighted Inverse Document Frequency (1994)
| Venue: | Special Interest Groups and Information Process Society of Japan (SIG-IPSJ |
| Citations: | 16 - 0 self |
BibTeX
@INPROCEEDINGS{Tokunaga94textcategorization,
author = {Takenobu Tokunaga and Iwayama Makoto},
title = {Text Categorization Based on Weighted Inverse Document Frequency},
booktitle = {Special Interest Groups and Information Process Society of Japan (SIG-IPSJ},
year = {1994},
pages = {33--39}
}
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Abstract
This paper proposes a new term weighting method called weighted inverse document frequency (WIDF). As its name indicates, WIDF is an extension of IDF (inverse document frequency) to incorporate the term frequency over the collection of texts. WIDF of a term in a text is given by dividing the frequency of the term in the text by the sum of the frequency of the term over the collection of texts. WIDF is applied to the text categorization task and proved to be superior to the other methods. The improvement of accuracy on IDF is 7.4% at the maximum.
