摘要
WAF(词激活力)是一种基于统计的描述词与词关系的算法,WAF不单纯是考虑的词之间的关联,还考虑了词前后顺序,词与词之间的距离,包含了概率和语言规则两种信息量。本文提出一种实体结构化数据的关系特征抽取算法,并基于该特征实现实体聚类。首先提取出实体结构化数据的语义和语境特征,以此来文本建模,然后对每个属性基于WAF值进行相似度计算,最后进行实体聚类。
WAF （word afifnity force） is algorithm based on a description of the proposed statistical relationships between words algorithm, WAF is not a simple association between the word consider, also consider the distance around the word’s order, between words, including the probability and amount of information in two language rules.propose entity feature extraction algorithms based on structured data and information extraction, themes for the use of the target entity subject extraction and classiifcation model, the following information for each topic extracted corresponding structural features, WAF value to calculate the similarity of each feature to the entity clustering.
出处
《软件》
2013年第12期148-151,共4页
Software
基金
111 Project of China under Grant No.B08004
key project of ministry of science and technology of China under Grant No.2011ZX03002-005-01
National Natural Science Foundation of China(61273217)
the Ph.D.Programs Foundation of Ministry of Education of China(20130005110004)
关键词
自然语言处理
实体特征抽取
实体关系挖掘
Nature Language Processing
Entity Feature Extraction
Entity Relation Mining
