JOURNAL ARTICLE

Chinese Web Text Classification System Model Based on Naive Bayes

Abstract

Web text classification is the process of determine the text types automatically under a given classification, according to the text content. Web text categorization system is the use of machine learning, knowledge engineering and other related fields of knowledge, access to the web on the text, after text preprocessing, Chinese word segmentation and training classifier, using classification algorithm to implement automatic classification. This paper designed a web of Chinese text categorization system model and system tested, experimental results show that the classification system of the web text categorization with two main characteristics which are efficiency and accuracy.

Keywords:
Computer science Artificial intelligence Naive Bayes classifier Preprocessor Categorization Text categorization Classifier (UML) Web query classification Text graph Text segmentation Natural language processing Data pre-processing Information retrieval Text mining Machine learning Segmentation Support vector machine Search engine Web search query

Metrics

22
Cited By
0.80
FWCI (Field Weighted Citation Impact)
9
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Text and Document Classification Technologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Computational Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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