基于邻居网络的科学文献关键词提取  

Keyphrase Extraction from Research Papers Using Neighborhood Networks

作　　者：黄晓玲[1,2] 王浩[1] 李磊[1] 伏明兰[1] HUANG Xiaoling;WANG Hao;LI Leil;FU Minglan(School of Computer Science and Information Engineering,Hefei University of Technology,Hefei 230009;School of Computer and Information Engineering,University,Chuzhou 239000)

机构地区：[1]合肥工业大学计算机与信息学院,合肥230009 [2]滁州学院计算机与信息工程学院,滁州239000

出　　处：《模式识别与人工智能》2018年第8期750-762,共13页Pattern Recognition and Artificial Intelligence

基　　金：国家重点研发计划项目(No.2016YFB1000901);国家自然科学基金项目(No.61503114);安徽省教育厅重点项目(No.KJ2017A418)资助~~

摘　　要：从单个文档中直接提取关键词不能满足关键词提取的精度要求,而现有基于邻居信息的关键词提取相关研究又耗时较长.因此,文中提出利用科学文献中共同作者关系以构建邻居网络,并联合使用这些邻居网络信息及文档本身内容提取关键词的方法.在此基础上,进一步提出利用领域知识中高频度共现词对以提取关键词,获得更高质量的关键词的方法.实验表明,文中方法性能较优.Extracting keywords directly from a single document cannot satisfy the precision requirements of keyphrase extraction, and the existing methods for keyphrase extraction based on neighbor information are time-consuming. In this paper, common author relations in research papers are utilized to build a neighbor network, and neighbor network information as well as document content is used to extract keyphrases. Based on those, high frequency pairs of phrase co-occurrence in domain are incorporated to further acquire high-quality keyphrases. Experimental results demonstrate that the proposed method is more computationally efficient than the existing methods.

关 键 词：共同作者网络 邻居网络 关键词提取 自然语言处理 文本处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]