关键词: 短信文本, 信息流, 热点事件, SinglePass, 聚类

Abstract:

The text information flow of SMS had carried abundant information resources. In order to find out the hot events behind it, an online sorting algorithm was  given for the text information flow of SMS. This method  used the cooccurrence frequency of feature words to define its relevance. And the similarity of message texts was  defined on the basis of preamble information collection and information frequency. Furthermore, after each time period of clustering,  the clustered SMS texts were classified periodically. This algorithm had higher efficiency to find hot events for a large number of short text information retrieval. Moreover, this algorithin  reduced the possibility of false detection and missed detection. Based on the comparison of experiments on algorithms between real data sets and SinglePass, the  results  showed that  each index was improved to some degree.

Key words: short message text, information flow, hot event, SinglePass, clustering