Research Article Open Access

Knowledge-based System of Indian Culture using Ontology with Customized Named Entity Recognition

Harsh Raj1, Kumar Harsh1, Payal Khattri1 and Tanwir Uddin Haider1
  • 1 National Institute of Technology Patna, India

Abstract

Indian culture is a blend of diversified ethics with different cultures and religions. There arise the sustainable challenges for the people of inter societies and religions to participate in the regional events with lack of cultural information like types of cuisines eaten; rituals followed etc. The existing search engines using a keyword-based approach make it difficult for people to find relevant information among millions of undesirable results. To overcome this problem, we applied the concept of the semantic web that facilitates unstructured data that is represented more precisely by using well-defined vocabularies such as Resource Description Framework (RDF), which is recognized by both people and machines. In this research, we have developed a Knowledge Base System (KBS) using an ontological approach (Ontology Development 101) integrating the concept of Customized Named Entity Recognition (CNER) that supports full-text query searching with structured information. To test the feasibility, several queries from our domain taken from different users were executed successfully. The precision of 0.96 justifies the efficacy of our framework. Finally, the evaluation results were compared with two previous methodologies which show that our methodology outperforms.

Journal of Computer Science
Volume 18 No. 3, 2022, 172-186

DOI: https://doi.org/10.3844/jcssp.2022.172.186

Submitted On: 16 July 2021 Published On: 30 March 2022

How to Cite: Raj, H., Harsh, K., Khattri, P. & Haider, T. U. (2022). Knowledge-based System of Indian Culture using Ontology with Customized Named Entity Recognition. Journal of Computer Science, 18(3), 172-186. https://doi.org/10.3844/jcssp.2022.172.186

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Keywords

  • Natural Language Processing
  • Ontology
  • Customized Named Entity Recognition
  • SPARQL
  • Knowledge Base