基于石油领域本体的概念相似度级联模型  

Cascade Model for Semantic Similarity of Concept Based on Petroleum Ontology

作　　者：赵国梁 宫法明[1] ZHAO Guo-Liang;GONG Fa-Ming(College of Computer ＆Communication Engineering, China University of Petroleum, Qingdao 266580, Chin)

机构地区：[1]中国石油大学(华东)计算机与通信工程学院,青岛266580

出　　处：《计算机系统应用》2018年第7期182-187,共6页Computer Systems & Applications

基　　金：科技部创新方法工作专项资助(2015IM010300);北京市重点实验室开放课题(BKBD-2017KF07)~~

摘　　要：提出了一种利用级联模型来计算本体中概念间相似度的新方法.在模型的第一阶段,采用了基于距离的语义相似度计算方法,计算出概念对在本体中的路径得分;第二阶段,采用IC(Information Content)算法精确计算概念对间相似度得分,并利用概念的公共子代集合对算法进行了扩展;第三阶段我们采用了特征整合策略,将所有的相似性得分构建成特征向量来描述概念对,并且使用权重来平衡第一阶段与第二阶段的相似度结算得分.最后使用BP神经网络确定两个概念的相似性.我们对新提出的语义相似度算法进行了评估,并与现有的方法相比.实验结果表明,该方法有效提高相似度算法的准确性和科学性.This paper presents a new cascade architecture to calculate the similarity between concepts in the ontology.In the first stage of proposed model,we use path-based methods to calculate the concept of path score in the ontology.In the second stage,we use Information Content（IC）-based methods to obtain similarity scores of two extended concepts with further consideration of the two concepts of public parent set and public subset.In the third stage,we adopt a feature integration strategy to combine all the similarity scores derived from the ontology to construct various kinds of features to characterize each concept pair and using weights to balance the concept of first-stage-scores with the third-stage-scores.In the end,BP neural network is used to obtain the similarity of two concepts.This model has been evaluated and compared with existing methods when applied to the task of semantic similarity estimation.Experimental results show that the proposed method effectively improves the accuracy and scientificity of similar calculation.

关 键 词：级联模型 石油本体 BP神经网络 路径得分 IC得分 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]