Performance Analysis for the Ontology based Intelligent Information Retrieval using Non Monotonic Inference Logic using SPARQL
- 1 Delhi Technological University, India
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.
Copyright: © 2017 Dr. Rajni Jindal and Alka Singhal. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Information Retrieval
- Non Monotonic Inference