Research Article Open Access

Performance Analysis for the Ontology based Intelligent Information Retrieval using Non Monotonic Inference Logic using SPARQL

Dr. Rajni Jindal1 and Alka Singhal1
  • 1 Delhi Technological University, India

Abstract

The paper proposes a model for the information retrieval system (E-library) for the learner, based on his current requirements and scenario. It follows a brokerage model using non monotonic logic utilizing semantics and ontology for object description. Ontology captures the learning object properties which can help in eliminating and evaluating the usefulness of the object for a given learner. Non monotonic logic helps in inferring the current usefulness of the learning object with current requirement and rules. It will vary the results with time and person. Therefore, it can provide better user oriented search.

Journal of Computer Science
Volume 13 No. 12, 2017, 694-701

DOI: https://doi.org/10.3844/jcssp.2017.694.701

Submitted On: 29 May 2017 Published On: 2 November 2017

How to Cite: Jindal, D. R. & Singhal, A. (2017). Performance Analysis for the Ontology based Intelligent Information Retrieval using Non Monotonic Inference Logic using SPARQL. Journal of Computer Science, 13(12), 694-701. https://doi.org/10.3844/jcssp.2017.694.701

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Keywords

  • E-Learning
  • Ontology
  • Information Retrieval
  • SPARQL
  • Non Monotonic Inference