Automatic Chinese Dialogue Text Summarization Based On LSA and Segmentation

Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis (LSA) is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an approach of automatic text segmentation analogous to TextTiling is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some 'important' sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results show that our approach is high efficient and improves significantly the coherency of the summary while not compromising informativeness.