DocumentCode
2141477
Title
Statistical Evaluation of Measure and Distance on Document Classification Problems in Text Mining
Author
Goto, Masayuki ; Ishida, Takashi ; Hirasawa, Shigeichi
Author_Institution
Musashi Inst. of Technol., Yokohama
fYear
2007
fDate
16-19 Oct. 2007
Firstpage
674
Lastpage
673
Abstract
This paper discusses the document classification problems in text mining from the viewpoint of asymptotic statistical analysis. By formulation of statistical hypotheses test which is specified as a problem of text mining, some interesting properties can be visualized. In the problem of text mining, the several heuristics are applied to practical analysis because of its experimental effectiveness in many case studies. The theoretical explanation about the performance of text mining techniques is required and this approach will give us very clear idea. The distance measure in word vector space is used to classify the documents. In this paper, the performance of distance measure is also analized from the new viewpoint of asymptotic analysis.
Keywords
classification; data mining; statistical testing; text analysis; asymptotic statistical analysis; distance measure; document classification; statistical evaluation; statistical hypotheses test; text mining; word vector space; Extraterrestrial measurements; Frequency measurement; H infinity control; Information retrieval; Information technology; Parametric statistics; Performance analysis; Testing; Text categorization; Text mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on
Conference_Location
Aizu-Wakamatsu, Fukushima
Print_ISBN
978-0-7695-2983-7
Type
conf
DOI
10.1109/CIT.2007.171
Filename
4385162
Link To Document