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Ontology Generation through the Fusion of Partial Reuse and Relation Extraction

机译:通过融合部分重用和关系提取的本体生成

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Ontology generation - a process to automatically create ontologies from existing knowledge sources - has become a key issue with the emergence of the semantic web. Though many researchers are trying to automate this process by exploiting machine learning and data mining techniques, the results remain under exploration. At the same time, when more and more ontologies are available online, it is important to reuse existing ontologies to a certain extent. In this paper, we present a semi-automatic ontology generation system (OntoGenerator) by partially reusing existing ontologies via a modularization technique and a ranking strategy. In order to enrich the semantics of the generated ontology, we integrate natural language-based, non-taxonomic relation extraction into the system. OntoGenerator is aimed at supporting ontology reuse in semantic indexing. Another objective is to evaluate the maturity of the semantic web by applying its technologies in ontology generation.
机译:本体生成 - 自动创建现有知识源的本体的过程 - 已成为语义网络的出现的关键问题。虽然许多研究人员正在尝试通过利用机器学习和数据挖掘技术来自动化这一过程,但结果仍然探索。与此同时,当在线提供越来越多的本体中,重要的是在一定程度上重复使用现有的本体。在本文中,我们通过模块化技术和排名策略部分地重复使用现有本体和排名策略,介绍半自动本体生成系统(Ontenerator)。为了丰富所生成的本体学的语义,我们将基于语言的非分类学关系提取整合到系统中。 Ontogererator旨在支持语义索引中的本体重用。另一个目标是通过在本体生成中应用其技术来评估语义网的成熟度。

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