NDLI: Exploring the use of fuzzy signature for text mining

Content Provider	IEEE Xplore Digital Library
Author	Kok Wai Wong Chumwatana, T. Tikk, D.
Copyright Year	2010
Description	Author affiliation: School of Information Technology, Murdoch University, South St, WA 6150, Australia (Kok Wai Wong; Chumwatana, T.) \|\| Institute for Computer Science, Humboldt-Univerität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany (Tikk, D.)
Abstract	The classical approaches for the traditional problems of text mining, such as document indexing, document clustering or text classification, represent the text as bag-of-words. Words, the units of the representation, are determined by tokenization, using e.g. whitespace and punctuation characters as separator. The bag-of-word based methods face problem with non-segmented text typical for some Asian languages, since the tokenization based solution cannot be applied anymore to determine the representation units. Several solutions were proposed so far, among them frequent max substring mining is adopted here because of its language-independency and favourable speed and store requirements. We present in this paper a fuzzy signature based solution using frequent max substring for non-segmented document representation, and propose how it could be applied for some typical text mining tasks. We show how the flexibility of fuzzy signatures can be exploited for text mining tasks. With the use of this proposed concept, complex decision models in text mining may be constructed more effectively in future.
Starting Page	1
Ending Page	5
File Size	162952
Page Count	5
File Format	PDF
ISBN	9781424469192
ISSN	10987584
e-ISBN	9781424469215
DOI	10.1109/FUZZY.2010.5584873
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-18
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Education Fuzzy sets Humans Lattices Medals Indexing Support vector machine classification
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Theoretical Computer Science Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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