Cognitive-Based Multi-document Summarization Approach

Automatic text summarization is an important and useful research area in natural language processing and information retrieval. Most of current approaches for text summarization do not make full use of human reading process. This paper proposes a multi-document scanning mechanism by simulating human reading process. The mechanism simulates human memory of words, association between words and three cognitive processes invoked when reading. Changes of human memory of topic words in reading process are used to denote sentences´ significance, based on which sentences are then ordered and extracted to form a summary. Experiments on DUC2007 test data show that our proposing method is efficient and outperforms two baseline methods.