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Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 559-563
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.
text classification; machne learning; KNN
Zengmin Geng, Jujian Zhang, Jianxia Du, Xuefei Li, "Research on Domain-Specific Text Classifier", Computer Science and Information Engineering, World Congress on, vol. 05, no. , pp. 559-563, 2009, doi:10.1109/CSIE.2009.22
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