| dc.contributor.author |
Doan, S. |
|
| dc.contributor.author |
Q.T, Ha |
|
| dc.contributor.author |
Horiguchi, S. |
|
| dc.date.accessioned |
2011-05-09T05:43:14Z |
|
| dc.date.available |
2011-05-09T05:43:14Z |
|
| dc.date.issued |
2006 |
|
| dc.identifier.citation |
Volume: 4223 LNAI, Page : 611-620 |
vi |
| dc.identifier.isbn |
3540459162; 9783540459163 |
|
| dc.identifier.issn |
3029743 |
|
| dc.identifier.uri |
http://tainguyenso.vnu.edu.vn/jspui/handle/123456789/7234 |
|
| dc.description.abstract |
In this paper we develop the general framework for text representation based on fuzzy set theory.
This work is extended from our original ideas [5],[4], in which a document is represented by a set of fuzzy
concepts. The importance degree of these fuzzy concepts characterize the semantics of documents and can
be calculated by a specified aggregation function of index terms. Based on this representation, a general
framework is proposed and applied to text categorization problem. An algorithm is given in detail for
choosing fuzzy concepts. Experiments on the real-world data set show that the proposed method is superior
to the conventional method for text representation in text categorization. ?? Springer-Verlag Berlin
Heidelberg 2006. |
vi |
| dc.language.iso |
en |
vi |
| dc.publisher |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
vi |
| dc.subject |
Algorithms |
vi |
| dc.subject |
Computational methods |
vi |
| dc.subject |
Data structures |
vi |
| dc.subject |
Functions |
vi |
| dc.subject |
Fuzzy sets |
vi |
| dc.subject |
Semantics |
vi |
| dc.subject |
Data sets |
vi |
| dc.subject |
Documents |
vi |
| dc.subject |
Text categorization |
vi |
| dc.subject |
Text processing |
vi |
| dc.title |
A general fuzzy-based framework for text representation and its application to text categorization |
vi |
| dc.type |
Article |
vi |