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
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;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.669
