Development of Background Ontology for Weather Systems through Ontology Learning
Ramar Kaladevi1, Appavoo Revathi2, Sivakumar Sridhar3

1Ramar Kaladevi , Associate Professor, Saveetha Engineering College.
2Appavoo Revathi, Associate Professor, Saveetha Engineering College.
3Sivakumar Sridhar, Assistant Professor, University College of Engg, Thirukkuvalai.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 168-172 | Volume-8 Issue-5, January 2020. | Retrieval Number: D4334118419/2020©BEIESP | DOI: 10.35940/ijrte.D4334.018520

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Abstract: Background or reference ontology is a common vocabulary for a system to share knowledge and support information integration. Weather system has more domain specific words, which are not fully covered by generic knowledge source like web and WordNet. For example, Temp is a word related with temperature in weather system, this kind meaning is not available in WordNet. Secondly, many new technical and scientific words are used and existing words also carry different senses. Thesauri usually cannot capture these new senses and words in time. Available background knowledge is insufficient to overcome the existing challenges and issues. This paper focuses on developing background ontology for weather system by enhancing existing knowledge bases. Finally the comparison is made between manually developed ontology and semi automatically developed ontology.
Keywords: Knowledgebase, Reference ontology, Semantic web, Ontology mapping.
Scope of the Article: Knowledge-based and Expert Systems.