摘要
从网上收集相关的文本信息,用ICTCLAS进行分词,用Java编程处理、转化为Weka的ARFF格式,再利用String To Word Vector过滤器转换为向量矩阵,最后用三种分类器分别进行分类的股票信息文本分类方法。实验表明取得了不错的效果。
This paper uses the variation coefficient method to measure economic disparity, and conducts an in-depth analysis of the industrial structure and economic differences. It is found that the second and third industry made greater contribution to people's income growth in Fuzhou and Xiamen regions. Gini coefficient method is employed to calculate total Gini coefficient, industrial Gini coefficient, industrial contribution to the regional economy, structural effects, geographic concentration effects; the results show that regional differences of pilot zones have been increasingly more marked, and the third industry has greater effect on the imbalanced regional development. The geographic concentration has intensified the regional economic difference. This paper aims to identify the underlining causes of the differences between the three regions before they were admitted into the pilot free trade zone and to narrow the gap between the three regions and find strategies for coordinated development of the pilot free trade zone.
出处
《福建师大福清分校学报》
2016年第2期64-67,共4页
Journal of Fuqing Branch of Fujian Normal University
基金
福建省自然科学基金面上项目(2015J01244)
福建省教育厅A类项目(JA14341)
关键词
股票文本
ICTCLAS
文本分类
economic differences
Fu Jian Pilot FTA
coordinated industrial development