원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.8 No.2
2015.02
pp.35-44
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Due to the complex market environment, it is very difficult to get the accurate predict of the stake only by the data analysis method. This paper uses the text categorization method to predict the trend of the stock. We divide the text categorization method into the following three steps: Text representation, Feature selection and Text Categorization. By comparing several categorization methods including feature selections and feature spaces, etc., the results show that the SVM method with Information Gain and 1000 feature spaces can get the better performance for the predict of the stock with the news.
목차
Abstract
1. Introduction
2. Text Representation
2.1. Related Works
2.2. Text Preprocessing
2.3. Feature Representation
3. Feature Selection Methods
3.1. IG (Information Gain)
3.2. CHI Square Statistics
3.3. Mutual Information (MI)
3.4. Expected Cross Entropy (ECE)
4. Text Categorization Methods
4.1. K Nearest Neighbors (KNN)
4.2. Support Vector Machine (SVM)
5. Analysis and Result
5.1. Text Collections
5.2. Evaluation Measures
5.3. Analysis
5. Conclusion
Acknowledgements
References
1. Introduction
2. Text Representation
2.1. Related Works
2.2. Text Preprocessing
2.3. Feature Representation
3. Feature Selection Methods
3.1. IG (Information Gain)
3.2. CHI Square Statistics
3.3. Mutual Information (MI)
3.4. Expected Cross Entropy (ECE)
4. Text Categorization Methods
4.1. K Nearest Neighbors (KNN)
4.2. Support Vector Machine (SVM)
5. Analysis and Result
5.1. Text Collections
5.2. Evaluation Measures
5.3. Analysis
5. Conclusion
Acknowledgements
References
저자정보
참고문헌
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