DocumentCode
2904305
Title
Kernel space for text analysis based on fuzzy neighborhoods
Author
Miyamoto, Sadaaki ; Kawasaki, Yuichi
Author_Institution
Dept. of Risk Eng., Tsukuba Univ., Tsukuba
fYear
2008
fDate
1-6 June 2008
Firstpage
738
Lastpage
743
Abstract
A natural Euclidean space is defined on a set of texts as sequences or hierarchical structures. Unlike the traditional term-document model, the present model takes local topological structure of texts. Kernel functions are defined that enable the use of Euclidean spaces and hence methods of data analysis based on kernels are applicable to the present model. Applications include agglomerative as well as c-means clustering and principal component analysis. Numerical examples are shown.
Keywords
data analysis; data mining; fuzzy set theory; geometry; text analysis; c-means clustering; data analysis; fuzzy neighborhoods; hierarchical structures; kernel functions; kernel space; local topological structure; natural Euclidean space; principal component analysis; text analysis; Data analysis; Equations; Fuzzy sets; Kernel; Principal component analysis; Support vector machine classification; Support vector machines; Text analysis; Text mining; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1098-7584
Print_ISBN
978-1-4244-1818-3
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2008.4630452
Filename
4630452
Link To Document