关键词: 关键短语提取, 文本特征, 互信息, 主题分析

Abstract: The SegPhrase algorithm is the state-of-art algorithm for key phrases extraction. It can get higher precision and recall in key phrases extraction than existing methods. However, SegPhrase algorithm has some shortcomings in key phrases extraction and their quality evaluation. In order to improve the quality of key phrases extraction and achieve effective Chinese key-phrase extractions, the SegPhrase algorithm is improved in this paper. In the phase of phrase generation, the mutual information feature between words is applied to preserve some low-frequency but important phrases. In the phase of phrase quality evaluation, different weights are assigned to different phrases to make the comprehensive assessment of the phrase. Then, the phrases that are more suitable to the context are selected. Finally, in order to verify the quality of the extracted key phrases, the extracted key phrases are applied to the topic analysis. Experiments show that the improved SegPhrase algorithm has higher recall and precision than the original method. The topic analysis results using the key phrases are more accurate than those based on keys, and can express the topic information of the document clearly.

Key words: key phrase extraction, text feature, mutual information, topic analysis