一种面向中文本体模式的本体对齐框架

Linking Chinese Open Data at Schema-Level

【目的】现有的本体对齐方法往往忽视中文概念的语序敏感和一词多义的语义特征。本文提出一种基于同义词词林和序列比对算法的大规模中文本体映射模型。【方法】采用基于改进的同义词词林相似度算法计算简单词元的语义相似度。并利用基于改进同义词词林与序列比对相融合的算法度量未登录词之间的语义相似度。【结果】在由DBpedia（中文版）、百度百科和互动百科知识库所构建的测试语料上的关联映射实验结果表明，该模型的准确率、召回率和综合评价指标平均分别达到约97．5％、87．8％和92．1％。【局限】本模型仅专注于对中文本体概念的元素级相似度度量，并未考虑本体属性和实例对于概念等价关系的影响因素。【结论】在面向中文网络百科的大规模开放语义数据集上的评测结果证明，该模型的总体性能明显优于现有算法。

[Objective] This study proposes a novel Chinese Ontology Mapping model based on TongYiCiCiLin （TYCCL） and Sequence Alignment to evaluate concept similarity of the Linked Chinese Open Data at Schema-Level. [Methods] Firstly, we modified the TYCCL-based algorithm to compute the similarity among atomic Chinese concepts from the TYCCL. Secondly, we proposed a global sequence-alignment algorithm to evaluate the similarity among Chinese OOV. [Results] The proposed model was examined with the corpus from DBpedia （Chinese version）, Baidu baike and Hudong knowledge base. The Precision, Recall and Fl-value of this model were 97.5%, 87.8% and 92.1%, respectively. [Limitations] The proposed model only measured the similarity among Chinese Ontology concepts at the element level, which did not evaluate the impacts of Ontology attributes and instance on the concept equivalence relationship. [Conclusions] The proposed model is better than existing ones.