CAJ | 학술논문

微博热点话题发现是目前的研究热点。针对传统热词抽取方法难以适用于微博数据的问题,提出一种基于老化理论的词生命值计算模型用于热词抽取,并基于热词间的相关性构建词共现网络；针对传统的词聚类算法不能较好地解决话题间存在重叠热词以及时间效率不佳的问题,引入多标签传播思想,设计一种接近线性时间复杂度的多标签传播聚类算法( TCMLPA)用于词共现网络的热词聚类,获得热点话题集。实验结果表明,词生命值计算模型能够有效过滤噪声并提取热词,TCMLPA算法则能够在保证聚类结果稳定性的情况下,有效提高热点话题发现的精度和效率。
미박열점화제발현시목전적연구열점。침대전통열사추취방법난이괄용우미박수거적문제,제출일충기우노화이론적사생명치계산모형용우열사추취,병기우열사간적상관성구건사공현망락；침대전통적사취류산법불능교호지해결화제간존재중첩열사이급시간효솔불가적문제,인입다표첨전파사상,설계일충접근선성시간복잡도적다표첨전파취류산법( TCMLPA)용우사공현망락적열사취류,획득열점화제집。실험결과표명,사생명치계산모형능구유효과려조성병제취열사,TCMLPA산법칙능구재보증취류결과은정성적정황하,유효제고열점화제발현적정도화효솔。
With the rapid growth of microblog data, extracting hot topics from vast amounts of microblog posts has become a research hotspot. The traditional methods for hot term extraction can hardly apply to microblog data, thus a life value calculation model based on aging theory is established to extract hot terms. Then, a hot term co-occurrence network is built based on the correlations between hot terms. Aiming at the problem that traditional clustering methods can hardly handle the hot term overlap between different topics and can not deal with vast amounts of data efficiently, a term clustering method based on multi-label propagation algorithm ( TCMLPA) , which has a nearly linear time complexity, is proposed to detect hot topics in hot term co-occurrence network. The experimental results show that life value calculation model can filter noise and extract hot terms effectively. Meanwhile, TCMLPA ensures the stability of clustering result and improves the accuracy and efficiency of hot topic detection.