@inproceedings{9a436ea980fa46ea8893cc0cfd9cf0a9,
title = "Iterative evolution of feature space in text classification",
abstract = "Nature language processing is an important part in data mining, which counts a lot in the internet age. Feature extraction effects the accuracy of text classification. This paper proposes a method of iterative feature space evolution to optimize the result. Adjusting the extended dictionary and the stop word list, we optimize the feature space time and again to get a better classifier model. The final result has a higher classification accuracy than the original experiment.",
keywords = "SVM, feature extraction, feature space, text classification",
author = "Liutao Zhao and Yitian Ren and Bo Yan",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 8th International Congress on Image and Signal Processing, CISP 2015 ; Conference date: 14-10-2015 Through 16-10-2015",
year = "2016",
month = feb,
day = "16",
doi = "10.1109/CISP.2015.7408065",
language = "English",
series = "Proceedings - 2015 8th International Congress on Image and Signal Processing, CISP 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1210--1214",
editor = "Lipo Wang and Sen Lin and Zhiyong Tao and Bing Zeng and Xiaowei Hui and Liangshan Shao and Jie Liang",
booktitle = "Proceedings - 2015 8th International Congress on Image and Signal Processing, CISP 2015",
address = "United States",
}