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Upper–Level Task Ontology for Generic Ontology Verbalization

机译:泛级任务本体进行泛型本体文体化语言

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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.
机译:语义技术在当代计算机科学家跨越各个领域的问题变得非常受欢迎。当表示基于语义的基于Web的知识模型以举例说明与特定域相关的知识,该知识被称为本体。研究人员已经精确地,本体是域名丰富的概念化。这就是为什么有成千上万的本体在线存储库中有关的内容,与医学,法律,管理等多个领域相关,即使是与可重用性和知识传播相关的最大瓶颈是在理解它的模式方面的复杂性为知识检索编写复杂的SPARQL或SQWRL查询的必要性,对每个人来说都不是可行的。因此,解决这种差距,这项研究侧重于设计上级任务本体,以管理RDF和猫头鹰格式的自然语言中的普通本体文明语言的整个过程。

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