Translated Title
Research and Performance Evaluation on the Theme Based Method for the Public Opinion Tracking
Translated Abstract
The aim of the public opinion tracking is to make tracks for the progress of the appointed hot topic in the information flow of the media, and this has becomes the hotspot research direction in the field of natural language processing in recent years. The key technique to achieve the task is text classification. The authors adopt different methods of information gain and mutual information for the feature selection within the vector space model. They are used for the weight calculation and the effective features with higher weight values are extracted. The approach of Rocchio, KNN and Bayes are adopted to implement the public opinion tracking on a given topic events. Finally, the authors give the statistical data analysis and achieve the performance of 86.2% F-Measure on the test set. Public opinion tracking has a broad application prospect in the areas of information security and so on. It provides the effective guidance for the determination to the development trend of the network hot events.
Translated Keyword
natural language processing
public opinion tracking
text classification
Access Number
WF:perioarticaltsqbgz201218010
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