Approach for Efficient Triple Pattern Extraction Information Retrieval in Ontology

Authors

  • Dr. K Chitra  Assistant Professor, Department of Computer Science, Govt. Arts College, Melur, Madurai, Tamilnadu, India
  • R Uma Maheswari  Assistant Professor, Department of CA&IT, Thiagarajar College, Madurai, India

DOI:

https://doi.org/10.32628/CSEIT228647

Keywords:

Ontology, Similarity Measurement, Visiting Frequency, Triple Pattern Extraction, Elearning

Abstract

E-learning is an effective tool for education than what is currently provided by any of the available computer aided tutoring, or learning management systems. Semantic Web is a collection of information that is linked to each other and process by machine in global scale. It can be seen as globally connected database. Here we proposed a combined methodology for better information retrieval by using similarity measurement and visiting frequency and triplet pattern extraction. The primary intention of this paper is to improve the learning capability. triple patterns extraction is essential to convert the incoming learners query to Ontology browsing query (SPARQL).After extracting the triple patterns from the input query is used to build the query for receiving exact information in the ontology content.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2022-12-30

Issue

Volume 8, Issue 6, November-December-2022

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. K Chitra, R Uma Maheswari, " Approach for Efficient Triple Pattern Extraction Information Retrieval in Ontology" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 6, pp.451-457, November-December-2022. Available at doi : https://doi.org/10.32628/CSEIT228647