Automatic Relationship Construction in Domain Ontology Engineering using Semantic and Thematic Graph Generation Process and Convolution Neural Network
Sivaramakrishnan R Guruvayur1, R.Suchithra2
1Sivaramakrishnan R Guruvayur, Department of Computer Science, Jain University, Karnataka, India.
2R.Suchithra, Department of Computer Science, Jain University, Karnataka, India.
Manuscript received on 11 August 2019. | Revised Manuscript received on 14 August 2019. | Manuscript published on 30 September 2019. | PP: 4602-4611 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6832098319/2019©BEIESP | DOI: 10.35940/ijrte.C6832.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In recent studies, Ontology construction plays an important role in translating raw text into useful knowledge. The proposed methodology supports efficient retrieval using multidimensional theory and implements integrated data training techniques before enter the trial process. The proposed approach has used the Semantic and Thematic Graph Generation Process to extract useful knowledge, and uses data mining techniques and web solutions to present knowledge as well as improve search speed and information retrieval accuracy. Established ontology can help clarify what it means for different ideas and relationships. Due to the rise of the ontology repository, the process of matching can take a long time. To avoid this, the method produces a hierarchical structure with in-depth interpretation of the data. A system is designed to remove domain dependencies using a dynamic labeling scheme using basic theorem, and the results show that it is possible to automatically and independently construct an independent domain.
Index terms: Automatic Ontology Generation, Semantic Web, Semantic Graph Generation, Thematic Graph Generation Process and Convolution Neural Network.
Scope of the Article: Semantic Web