DocumentCode :
495255
Title :
Research on Domain-Specific Text Classifier
Author :
Geng, Zengmin ; Zhang, Jujian ; Li, Xuefei ; Du, Jianxia
Author_Institution :
Comput. Inf. Center, Beijing Inst. of Fashion Technol., Beijing, China
Volume :
5
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
559
Lastpage :
563
Abstract :
For resolving the low classification efficiency to domain-specific documents for traditional text categorization algorithms (like KNN, SVM and etc), this paper presents a new text classifier with high performance oriented domain-specific documents. The algorithm is mainly depended on the weight and weight factor of hierarchy feature words in documents. Different hierarchy feature words which have different weights are collected by processing to corpus and classification tree. The weight factor is gained by machine learning method to corpus and knowledge base. Classification experiment to metrological documents shows that new classifier outperforms the KNN.
Keywords :
knowledge based systems; learning (artificial intelligence); text analysis; domain-specific text classifier; high performance oriented domain-specific document; knowledge base system; machine learning method; text categorization algorithms; Classification tree analysis; Computer science; Frequency; High performance computing; Learning systems; Machine learning algorithms; Metrology; Support vector machine classification; Support vector machines; Text categorization; KNN; machne learning; text classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.22
Filename :
5170597
Link To Document :
بازگشت