An automatic system for Chinese news summarization

摘要

With the popularity of Internet, information overloading has become a major problem. Text summarization, which tries to reduce the amount of the content without losing the principle meaning of the content, could reduce the information overloading problem effectively. In this paper, a Chinese news automatic summarization system is proposed to summarize Chinese news. The main purpose of this system is to extract the most important sentences from the news. Term frequency is used to determine the importance of terms and the sentences' weighting could be obtained from the summarization of the term weightings. In addition, edit distance algorithm is used to measure the similarity among news title and the sentences and the similarity comparison result will be another weighting factor of the sentences selection. Finally, redundant sentences will be removed based on similarity comparison.