Kaneeka. Vidanage, Noor Maizura Mohamad, R. Mohemad
{"title":"Upper–Level Task Ontology for Generic Ontology Verbalization","authors":"Kaneeka. Vidanage, Noor Maizura Mohamad, R. Mohemad","doi":"10.1109/IRCE.2019.00037","DOIUrl":null,"url":null,"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.","PeriodicalId":298781,"journal":{"name":"2019 2nd International Conference of Intelligent Robotic and Control Engineering (IRCE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference of Intelligent Robotic and Control Engineering (IRCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRCE.2019.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.