OntoJob Query Processor: An Ontology Driven Query Processing Method in Jobology Information System
- 1 J.C. Bose University of Science and Technology, India
Abstract
There are a large numbers of jobsites/job portals that provide information about employment on the internet. These websites facilitate employers to post job lists. Job seekers go through those job posts and apply for the same. But, due to the availability of dozens of job portals, job seekers are unable to concentrate on the efforts to see the best outcomes. The overall objective of the paper is to develop a prototype system that provides a platform for the job seeker to access all the job lists from various job sites on a single click, at the same place with respect to the fired query. For this purpose, an ontology driven information system named as Jobology is discussed that integrates various Jobboards using the approach of ontology alignment. The system takes user’s query in keyword format and in response generates a set of SPARQL queries. These SPARQL queries are then fired on their respective ontologies and in turn they yield the results. These results are merged and finally presented to user. As a contribution of this paper, we have proposed an “OntoJob” Query processor that takes job seeker query in keyword format and in turn generates a set of SPARQL queries with respect to every jobboard. The proposed approach is implemented in JAVA using OWLAPI on window platform. To evaluate the proposed work, comparison analysis between Jobboards, proposed ontologies and integrated system was performed. The results came out to be very satisfactory.
DOI: https://doi.org/10.3844/jcssp.2020.702.714
Copyright: © 2020 Ranjna Jain and Neelam Duhan. 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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Keywords
- Ontology
- Semantic Web
- Data Heterogeneity
- Query Processing
- SPARQL