一种局部与全局特征相结合的主题域识别模型  

A Topic Domain Identification Model Combining Local and Global Characteristics

作　　者：寇月 徐宏斌 申德荣 聂铁铮 KOU Yue;XU Hong-bin;SHEN De-rong;NIE Tie-zheng(School of Computer Science ＆ Engineering,Northeastern University,Shenyang 110169,China.)

机构地区：[1]东北大学计算机科学与工程学院,辽宁沈阳110169

出　　处：《东北大学学报（自然科学版）》2018年第2期176-180,共5页Journal of Northeastern University(Natural Science)

基　　金：国家重点基础研究发展计划项目(2012CB316201);国家自然科学基金资助项目(61472070);中央高校基本科研业务费专项资金资助项目(130404015)

摘　　要：传统的主题域识别技术主要局限于单一领域,缺乏领域间的交互式协同,难以保证识别结果的准确性,因此提出一种局部与全局特征相结合的主题域识别模型.该模型一方面基于实体在领域内的局部特征进行局部识别,另一方面基于领域间协同作用、领域相关度等全局特征对各个局部识别结果进行一致化趋近,从而使识别结果更全面、有效.另外,针对相似矩阵的更新时机、协同作用的量化以及迭代终止条件的设定三个方面对主题域识别算法进行了优化.通过实验验证了本文所提出的关键技术的可行性和有效性.Traditional identification techniques focus on a single domain and lack the mutual collaboration among different domains,which often lead to dumb results. So,a topic domain identification model combining local and global characteristics is proposed. Local identification is performed based on entities＇ local characteristics within one domain. On the other hand,these local identification results tend to be consistent with each other based on the global characteristics such as the collaboration and relevance among domains,which can maintain the accuracy of identification effectively. In addition,some improvements are made for the algorithm of topic domain identification,including similarity matrix updating,collaboration quantifying and iteration terminating. The experiments demonstrate the feasibility and effectiveness of the proposed model.

关 键 词：主题域识别 交互式协同 局部特征 全局特征 领域相关度 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]