Design and Implementation of News-Oriented Automatic Summarization System Based on Chinese RSS
Automatic summarization is an important research branch of natural language processing.The automatic summarization should provide information to users from different point of views for better understanding.Aiming at the characteristics of the news, an automatic summarization system is constructed from two aspects: keywords and key sentences.Then, the location factor is added to optimize the keywords extraction algorithm.Meanwhile, the key sentences extraction algorithm is improved through introducing keywords factors.On this basis, in allusion to the existing problems of RSS, this paper builds a user-interest model.Finally, after the verification in terms of the feasibility and the effectiveness, the result shows it is effective to improve the accuracy and the user experience of the RSS feeds.
Keywords extraction Key sentences extraction RSS feeds
Jie Wang Jie Ma Yingjun Li
College of Software, Nankai University, Tianjin, China Collage of Information Technology Science, Nankai University, Tianjin, China
国际会议
Second CCF Conference,NLPCC2013(第二届自然语言处理与中文计算会议)
重庆
英文
378-385
2013-11-15（万方平台首次上网日期，不代表论文的发表时间）