计算机技术与发展2019，Vol.29Issue(3)：12-17,6.DOI:10.3969/j.issn.1673-629X.2019.03.003
融合知识图谱和ESA方法的网络新词识别
Network New Word Recognition Based on Fusion of Knowledge Graph and ESA
摘要
Abstract
With the rapid development of the Internet, the use of Weibo, WeChat and other text forms is gradually increasing. The analysis and understanding of such texts has posed new challenges in the field of natural language processing, especially in the field of network neologism recognition and semantic understanding. In order to overcome the shortcomings of traditional methods that cannot identify network neologism and their semantics, we propose a new method of network neologism recognition by combining knowledge map and explicit semantic analysis methods, which segments the original text with the coarse-grained phrase to preserve the logical relationship between the words. After using the semantic expression phrase of the Baidu knowledge map Schema, the ESA method is used to gradually decompose the remaining texts and extract the phrase encyclopedia information into the core semantic vocabulary, supplementing the unrecognized part of the Schema. Experiment shows that compared with the existing neologism recognition algorithms, the proposed algorithm requires only a small amount of corpus, which reduces the cost of manual rules formulation and improves the recognition of network neologism and the accuracy of word comprehension.关键词
语义识别/语义相关度/新词识别/知识图谱/显性语义分析Key words
semantic recognition/semantic relevance/neologism recognition/knowledge graph/explicit semantic analysis分类
信息技术与安全科学引用本文复制引用
刘申凯,周霁婷,朱永华,高洪皓..融合知识图谱和ESA方法的网络新词识别[J].计算机技术与发展,2019,29(3):12-17,6.基金项目
国家重点研发计划专项课题(2017YFD0400101) （2017YFD0400101）
