Title :
Text categorization algorithms representations based on inductive learning
Author :
Jian-Fang, Cao ; Hong-bin, Wang
Author_Institution :
Dept. of Comput. Sci., Xinzhou Teachers Univ., Xinzhou, China
Abstract :
Text categorization-assignment of natural language texts to one or more predefined categories based on their content-is an important component in many information organization and management tasks. Categorization algorithm is the most critical factor to text categorization system performance. The inductive learning classifiers are put forward. Very accurate text categorization result can be learned automatically from training examples.
Keywords :
learning by example; natural language processing; pattern classification; text analysis; inductive learning classifiers; information organization; management tasks; natural language text assignment; text categorization algorithm representation; Classification tree analysis; Content management; Information filtering; Information filters; Information management; Learning systems; Machine learning; Natural languages; Testing; Text categorization; classification; inductive learnin; text categorization;
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
DOI :
10.1109/ICIME.2010.5477992