Automatic Abstracting Generating Based on Mobile Short Message Text Information Flow
Liu Jinling1, Ni Xiaohong2, Wang Xingong2
1. Computer Engineering Faculty, Huaiyin Institute of Technology, Huaian 223003, China; 2. Department of Computer, Cangzhou Teachers College, Cangzhou 061001, China
Abstract：Due to the characteristics of mobile short message text information flow in the practical application,an automatic digest generation model is designed. The model uses word co-occurrence to define the semantic similarity. Using the TF-IDF,weights of feature words and abstracts candidate sentence weights are defined in the model. By removing isolated points, the algorithm generates smaller redundancy and more readable short text messages flow digest according to the weight screening abstract and abstract sort. Experiments of the relevant data show that the model has better quality and higher efficiency in abstract generation.
刘金岭, 倪晓红, 王新功. 手机短信文本信息流的自动文摘生成[J]. 现代图书情报技术, 2013, 29(2): 43-49.
Liu Jinling, Ni Xiaohong, Wang Xingong. Automatic Abstracting Generating Based on Mobile Short Message Text Information Flow. New Technology of Library and Information Service, 2013, 29(2): 43-49.
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