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News Web Texts Classification Based on Contents

Author: PanZhengGao
Tutor: HuXueGang
School: Hefei University of Technology
Course: Applied Computer Technology
Keywords: Data Mining Entity Recognition Text Classification Feature selection
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 84
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Abstract


With the rapid development and popularity of the WWW , it has been a rapid transition from the era of information resources are scarce to extremely rich information of the digital age . The face of a flood of online information resources , it is difficult to quickly and effectively find the information . Therefore , how reasonable and effective organization and management of online information , has become an important research topic in the field of Web Intelligence . With the massive growth of the network information , the traditional manual processing network information can not adapt to the needs of the times . Most of the information on the network appears in text form . Therefore , the automatic classification of Web text has become an increasingly important area of ??research . This study mainly the following aspects: ( 1 ) analysis of the characteristics of Web text classification feature item extraction , classification and other key technology to explore and study the existing difficulties and outstanding problems . (2) a combination of rules and statistics Chinese named entity recognition method . A construct external and internal rules of probability and statistics , Chinese named entity recognition method , the experimental results show that this method can obtain a higher precision and recall rate . ( 3 ) discuss the limited role of the news Web News text entity elements of its theme . And is characterized by a combination of factors to these news entities , Web news text classification . The experimental results show that this method to obtain a better theme identification effect . ( 4) A News news entity elements as the feature to represent the Web news text model - SNE model classifier constructed on this basis . The experimental results show that the theme of the news entity elements on the basis of the model portfolio of Web news text classification method can achieve better classification results .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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