计算机科学 ›› 2016, Vol. 43 ›› Issue (9): 261-265.doi: 10.11896/j.issn.1002-137X.2016.09.052
朱明峰,叶施仁,叶仁明
ZHU Ming-feng, YE Shi-ren and YE Ren-ming
摘要: 当前,由于全民自媒体兴起而引发了巨大的舆情危机,如何高效快速地从海量的碎片化信息中发现热点并抽取实用信息成为一项重大的挑战。在此背景下,提出一种基于Lex-PageRank的微博摘要优化方法,在该方案中,以聚类结果作为实验数据,从微博影响力周期的时间特性和权重属性考虑,提出改进的Lex-PageRank算法,从聚类结果中抽取若干文本组织生成摘要。在新浪微博数据基础上进行的对比实验表明,本方案可以有效地从大量文本中提取出关键信息。
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