CAJ | 학술논문

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（사격활력）시일충기우통계적묘술사여사관계적산법,WAF불단순시고필적사지간적관련，환고필료사전후순서，사여사지간적거리，포함료개솔화어언규칙량충신식량。본문제출일충실체결구화수거적관계특정추취산법，병기우해특정실현실체취류。수선제취출실체결구화수거적어의화어경특정，이차래문본건모，연후대매개속성기우WAF치진행상사도계산，최후진행실체취류。
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.