大型复杂医学领域本体质量评估理论研究

项目名称： 大型复杂医学领域本体质量评估理论研究

项目编号： No.61502221

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 罗凌云

作者单位： 南华大学

项目金额： 21万元

中文摘要： 随着医学领域本体影响力的不断扩大，本体质量评估的重要性更加凸显。常用的医学领域本体规模大、结构复杂，导致现有的各质量评估方法很难得到系统化推广；评估结果验证过程中对专家知识的过分依赖也极大地降低了评估效率；此外，本体中概念的粒度划分不均问题一直未被纳入本体质量评估的范畴。针对以上问题，本项目拟首先借助图分割算法将本体分块，并以此评估其平衡度，接着利用形式化建模技术，建立系统的语义关系质量评估机制。此外，为了节省人力资源，拟提前运用专家知识筛选出可疑模型，再设计算法自动获取满足可疑模型的实例。最后，对可疑实例的确证将利用第三方数据自动完成。本项目的实施可为系统地评估医学领域本体中的语义关系以及自动验证评估结果提供新思路，同时为构建新本体提供参考规范，从而提高医学领域本体质量，保障医学信息系统的安全性。

中文关键词： 医学信息学；本体评估；生物医学领域本体；形式化方法；语义网

英文摘要： The expanding use of biomedical ontologies further demonstrates the importance of Ontology Auditing. As those commonly used biomedical ontologies are often large and complex, the existing Ontology Auditing methodologies tend to be neither general nor systematic enough. Furthermore, the evaluation process relies heavily on ontology expertise, which was shown to be non-efficient. Last but not least, the concept of ontology granularity checking was not proposed in the literature yet. To deal with the above challenges, we propose a methodology to leverage the use of graph partitioning to divide large ontology into smaller ones, based on which we can also do balance auditing of the ontology. Formal method will be used to establish a relation auditing mechanism in this project. Moreover, to relieve the burden on labor, instead of evaluating every instance with potential error, ontology experts will only help evaluating erroneous models. Erroneous instances will be retrieved automatically based on the models. At last, the evaluation will be completed using third-party data. Our research will shed light on the fields of systematically auditing semantic relations in biomedical ontologies, as well as automatically evaluating the results, thus improve the quality of biomedical ontologies, and secure medical systems.

英文关键词： Medical Informatics;Ontology Auditing;Biomedical Ontology;Formal Methods;Semantic Web