An Ensemble Classification Algorithm for Text Data Stream Based on Feature Selection and Topic Model
2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)(2020)
摘要
How to mine valuable information that users are interested in from a continuous text data stream, text data stream classification has received widespread attention as a core technology to solve the problem. This paper proposes a text data stream ensemble classification algorithm that combines feature selection and topic model. Firstly, the mutual information feature selection method is used to remove features that are not related to classification. Secondly, the LDA topic model is used to establish the document-topic distribution. Finally, the pre-processed text data stream is classified by an ensemble classification model. The experimental results show that the proposed text data stream ensemble classification algorithm can improve the classification performance of text data stream.
更多查看译文
关键词
text data stream,ensemble classification model,feature selection,topic model
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要