Upper–Level Task Ontology for Generic Ontology Verbalization

Kaneeka. Vidanage, Noor Maizura Mohamad, R. Mohemad
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Abstract

Semantic technologies have become very popular across contemporary computer scientists in resolving issues across a range of domains. When a semantic web-based knowledge model is represented to exemplify knowledge related to a particular domain, that is referred to as an ontology. Researchers have pinpointed, ontologies are domain rich conceptualizations. That‘s why there are thousands of ontologies already developed and available in online repositories relevant to multiple domains such as medicine, law, management and etc. Even though, the biggest bottlenecks linked with reusability and knowledge dissemination of ontologies are complexity in understanding it’s schema and necessity of writing complex SPARQL or SQWRL queries for knowledge retrieval, which is not feasible for everyone. Therefore, addressing that gap, this research focuses on designing an upper-level task ontology to govern the entire process of generic ontology verbalization in Natural language for both RDF and OWL formats.
通用本体语言化的上层任务本体
语义技术在当代计算机科学家中非常流行,用于解决一系列领域的问题。当一个基于web的语义知识模型被表示为与特定领域相关的示例知识时,它被称为本体。研究人员指出,本体是领域丰富的概念化。这就是为什么在线存储库中已经开发并提供了数千个与医学、法律、管理等多个领域相关的本体的原因。尽管如此,与本体的可重用性和知识传播相关的最大瓶颈是理解其模式的复杂性,以及为知识检索编写复杂的SPARQL或SQWRL查询的必要性,这并不是对每个人都可行。因此,为了解决这一差距,本研究的重点是设计一个上层任务本体来管理RDF和OWL格式的自然语言通用本体语言化的整个过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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