An automatic classification system for the stock comments

Shuyi Hong, Xue Han, L. Tian, Linkai Luo
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引用次数: 1

Abstract

The online stock comments are known to have some impacts on the trend of the stock market. In this paper, we design and implement an automatic classification system for the stock comments, which is an important issue in discussing the relation between the trend of the stock market and the stock comments. A classifier based on support vector machine (SVM) is established in which the topic words are considered as the features of the classification for the stock comments. The number of the topic words is only a few dozen because the topic words are only related to the online stock comments. Therefore, our system does not suffer from the curse of dimensionality which is a challenge in the common text classification. The experiment results on some datasets of the stock comments show our method is effective and can be regarded as an automatic tool for the classification of the stock comments.
股票评论的自动分类系统
众所周知,网上的股票评论会对股票市场的走势产生一些影响。本文设计并实现了一个股票评论自动分类系统,这是讨论股票市场趋势与股票评论之间关系的一个重要问题。建立了一种基于支持向量机(SVM)的分类器,将主题词作为股票评论分类的特征。主题词的数量只有几十个,因为主题词只与网上股票评论有关。这样,我们的系统就不会受到常见文本分类中存在的维度诅咒的困扰。在一些股票评论数据集上的实验结果表明,该方法是有效的,可以作为股票评论自动分类的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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