DocumentCode
508303
Title
Multi-labeled Chinese Text Categorization Based on the Boosting Algorithms
Author
Wang, Zhan ; Jiang, Minghu
Author_Institution
Sch. of Comput., Univ. of Utah, Salt Lake City, UT, USA
Volume
1
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
205
Lastpage
208
Abstract
This paper proposes approaches for multi-labeled text categorization based on the boosting algorithms.We discussed the performances of various feature selection methods for multi-labeled TC. Besides the multi-labeled categorization, we also make efforts on ranking the labels assigned to the texts.
Keywords
information retrieval; learning (artificial intelligence); natural language processing; text analysis; boosting algorithm; feature selection; information retrieval; multilabeled Chinese text categorization; Boosting; Cities and towns; Computational linguistics; Content based retrieval; Information retrieval; Information systems; Internet; Machine learning; Machine learning algorithms; Text categorization; Adaboost; information retrieval; machine learning; multi-label; text categorization;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.669
Filename
5366527
Link To Document