@inproceedings{99929281295943779bcbbb8cd8de8bb6,
title = "Using category-based semantic field for text categorization",
abstract = "This paper proposes a new document representation method to text categorization. It applies Category-based Semantic Field (CBSF) theory for text categorization to gain a more efficient representation of documents. The lexical chain is introduced to compute CBSF and Hownet* used as a lexical. database. In particular, the title of each document functions as a clue to forecast the potential CBSF of the test document. Combined with classifier, this approach is examined in text categorization and the result indicates that it performs better than conventional methods with features chosen on the basis of bag-of-words (BOW) system, on the same task.",
keywords = "Category-based Semantic Field (CBSF), Hownet, Lexical Chain, SVM",
author = "Qiang Wang and Yi Guan and Wang, \{Xiao Long\} and Xu, \{Zhi Ming\}",
year = "2005",
doi = "10.1109/ICMLC.2005.1527598",
language = "英语",
isbn = "078039092X",
series = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",
publisher = "IEEE Computer Society",
pages = "3781--3786",
booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",
address = "美国",
note = "International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",
}