DocumentCode
2041118
Title
Text mining with conceptual graphs
Author
Montes-y-gómez, M. ; Gelbukh, A. ; Lopez-Lopez, Alvaro ; Baeza-Yates, R.
Author_Institution
Centro de Investigacion en Computacion, Mexico
Volume
2
fYear
2001
fDate
2001
Firstpage
898
Abstract
A method for conceptual clustering of a collection of texts represented with conceptual graphs is presented. It uses an incremental strategy to construct the cluster hierarchy and incorporates some characteristics attractive for text mining purposes. For instance, it considers the structural information of the graphs, uses domain knowledge to detect the clusters with generalized descriptions, and uses a user-defined similarity measure between the graphs
Keywords
data mining; graph theory; pattern clustering; text analysis; cluster hierarchy; conceptual graphs; conceptual text clustering; domain knowledge; generalized descriptions; incremental strategy; structural information; text mining; user interest profile; user-defined similarity measure; Area measurement; Data mining; Extraterrestrial measurements; Machine learning; Natural languages; Optical computing; Pattern analysis; Text mining; Text processing; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location
Tucson, AZ
ISSN
1062-922X
Print_ISBN
0-7803-7087-2
Type
conf
DOI
10.1109/ICSMC.2001.973031
Filename
973031
Link To Document