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分解与BioPortal本体模块化结构

Decomposition and Modular Structure of BioPortal Ontologies
课程网址: http://videolectures.net/iswc2011_vescovo_klinov_structure/  
主讲教师: Chiara Del Vescovo, Pavel Klinov
开课单位: 曼彻斯特大学
开课时间: 2011-11-25
课程语种: 英语
中文简介:
我们首次对大量最先进的生物医学本体 (即 ncbo 生物门户存储中的生物技术) 中的生物医学本体的模块化结构进行了大规模的研究。生物门户本体转化为逻辑上连贯的子集 (原子), 这些子集通过依赖的概念相互关联。我们分析了生成的结构的各个方面, 并讨论了它们对本体应用的影响。例如, 我们描述和研究了这些本体分解的用法, 以提取模块, 例如, 促进 sswap (简单语义 web 体系结构和协议) 中语义 web 服务的匹配。这些服务的描述使用来自 biowportal 的术语, 因此服务发现需要对本体的相关片段 (即模块) 进行推理。我们提出了一种从分解的生物门户本体中提取模块的新算法, 该算法能够快速识别需要包含在模块中的原子, 以确保逻辑上完整的推理。与现有的模块提取算法相比, 它具有许多优点, 包括提高了性能和避免将整个本体加载到内存中的可能性。并对该算法进行了生物门户本体系统的评价, 并对其结果进行了介绍和讨论。
课程简介: We present the first large scale investigation into the modular structure of a substantial collection of state-of-the-art biomedical ontologies, namely those maintained in the NCBO BioPortal repository.5 Using the notion of Atomic Decomposition, we partition BioPortal ontologies into logically coherent subsets (atoms), which are related to each other by a notion of dependency. We analyze various aspects of the resulting structures, and discuss their implications on applications of ontologies. In particular, we describe and investigate the usage of these ontology decompositions to extract modules, for instance, to facilitate matchmaking of semantic Web services in SSWAP (Simple Semantic Web Architecture and Protocol). Descriptions of those services use terms from BioPortal so service discovery requires reasoning with respect to relevant fragments of ontologies (i.e., modules). We present a novel algorithm for extracting modules from decomposed BioPortal ontologies which is able to quickly identify atoms that need to be included in a module to ensure logically complete reasoning. Compared to existing module extraction algorithms, it has a number of benefits, including improved performance and the possibility to avoid loading the entire ontology into memory. The algorithm is also evaluated on BioPortal ontologies and the results are presented and discussed.
关 键 词: 生物医学本体; 本体论; 模块提取算法
课程来源: 视频讲座网
最后编审: 2020-06-28:yumf
阅读次数: 64