TY - GEN
T1 - Data mining method from text database
AU - Kawano, Masahiro
AU - Watada, Junzo
AU - Kawaura, Takayuki
PY - 2005
Y1 - 2005
N2 - Recently, various types of data are expected to get in information processing according to multi-media technology. Especially, linguistic data are employed in fuzzy systems as well as fuzzy numerical values. In this paper we propose a text minig method based on fuzzy quantification model. In the process of text mining, we will pursue the following steps: 1) Sentences included in a text in Japanese are broken down into words. 2) It is possible to realize common understanding using fuzzy thesaurus that enables us to translate words into synonyms or into upper concepts. In this paper, we employ the method to translate words using Chinese characters or continuous letters of Katakana more then one katakana letter (Japanese alphabet letter) into keywords. The method realizes the high speed of processing without any dictionary for separating words. Fuzzy multivariate analysis is employed to analyze such processed data and to abstract a latent mutual related structure under the data. In other words, we abstract the knowledge from the given text data. At the end we apply the method to mining the text information of libraries and Web pages distributed over a web network and discussing about the application to Kansei engineering.
AB - Recently, various types of data are expected to get in information processing according to multi-media technology. Especially, linguistic data are employed in fuzzy systems as well as fuzzy numerical values. In this paper we propose a text minig method based on fuzzy quantification model. In the process of text mining, we will pursue the following steps: 1) Sentences included in a text in Japanese are broken down into words. 2) It is possible to realize common understanding using fuzzy thesaurus that enables us to translate words into synonyms or into upper concepts. In this paper, we employ the method to translate words using Chinese characters or continuous letters of Katakana more then one katakana letter (Japanese alphabet letter) into keywords. The method realizes the high speed of processing without any dictionary for separating words. Fuzzy multivariate analysis is employed to analyze such processed data and to abstract a latent mutual related structure under the data. In other words, we abstract the knowledge from the given text data. At the end we apply the method to mining the text information of libraries and Web pages distributed over a web network and discussing about the application to Kansei engineering.
KW - Fuzzy quantification analysis
KW - Library data
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=33745304208&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745304208&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33745304208
SN - 3540288961
SN - 9783540288961
VL - 3683 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1122
EP - 1128
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
Y2 - 14 September 2005 through 16 September 2005
ER -