摘要
官方微博中混杂有较多无关其组织团体的信息,这为事件的提取与摘要工作带来了很大挑战.论文综合考虑官方微博数据的特性,提出了语料加权、标签识别的官方微博事件摘要模型,并结合官微相关语料提出了一种语料加权排序的关键词计算方法(Corpus Weighted Ranking,CWR),为博文相似度计算和事件摘要提供了基础支撑.实验测试表明,与IF-IDF和TextRank方法相比较,CWR在关键词提取正确率P,召回率R和F值表现更好,并在后期选取权重较大句子构成事件摘要时取得了很好的效果.
Official Microblog is the certified Microblog, whose account generally belongs to an organization. Its data are not only highlyreliable with clear-cut labels, but also have a strong social effect. To summarize the organhelp improve the reading efficiency . However,the official Microblog usually contains more information unrelated to the organization,which brings great challenges for event extraction and summary. The corpus-weighted and label-recognized model of official Microblog event summarization was proposed according to the characteristics of the official Microblog data, and keywords calculation method combined with the official relevant corpus was presented,providing a basic suppolog similarity calculation and event summarization. Experimental tests show that,compared with IF-IDF and TextRank method,CWRhave better performace in thematic term extraction precision rate P,the recall rate R and F value. And it achieved good results in thelater selecting weighted sentences for generating event summarization.
作者
高永兵
杨贵朋
张娣
GAO Yong-bing;YANG Gui-peng;ZHANG Di(Information Engineering School,Inner Mongolia University of Science and Technology,Baotou 014010, China)
出处
《内蒙古科技大学学报》
CAS
2017年第3期273-279,共7页
Journal of Inner Mongolia University of Science and Technology
基金
内蒙古自治区科学基金资助项目(2015MS0621)