Using Apache Jena Fuseki Server for Execution of SPARQL Queries in Job Search Ontology Using Semantic Technology
DOI:
https://doi.org/10.55524/Keywords:
Apache Jena Fuseki, Job Search, Ontology, Semantic Web, SPARQLAbstract
The "SPARQL Protocols as well as RDF Query Language" allows users to query information from a database or any other data source that can be mapped to RDF. The SPARQL standard, created and supported by the W3C, allows developers and users to concentrate on whatever they wants to know instead of how a database is organized. The proposed paper presents a Job Search Ontology to help the employers, by recommending the most eligible candidates for a particular job in IT domain and, on the other hand, to propose jobs to the aspiring candidates, matching their profiles with the existing job offers. This paper also discussed the continuous demand for qualified candidates in the Information Technology (IT) domain has empowered the use of e-Recruitment tools, which are becoming more and more exploited at the expense of the traditional methods in this paper. The major purpose of this research is to create an ontologies using the Protégé ontology construction tool, which is then used to run Simple Protocols as well as RDF (Resource Description Framework) Query Language (SPARQL) queries on it. This proposed system utilized Apache Jena Fuseki Server for execution of SPARQL queries for Job Search Ontology and it is very useful in upcoming days.
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S. Mishra and S. Jain, “A study of various approaches and tools on ontology,” 2015, doi: 10.1109/CICT.2015.43. [2] S. Malik, S. Mishra, N. K. Jain, and S. Jain, “Devising a Super Ontology,” 2015, doi: 10.1016/j.procs.2015.10.118.
S. Jain, R. Gupta, and R. K. Dwivedi, “Generating patterns from pizza ontology using protégé and weka tool,” 2018, doi: 10.1109/SYSMART.2018.8746935.
T. Rastogi, Z. Chowdhary, M. Krishna, S. Mehrotra, and R. Mohan, “Prevalence of periodontitis in patients with pulmonary disease: A cross-sectional survey in the industrial district of India,” J. Indian Soc. Periodontol., 2019, doi: 10.4103/jisp.jisp_435_18.
A. Walia, N. Singhal, and A. K. Sharma, “A novel e learning approach to add more cognition to semantic web,” 2015, doi: 10.1109/CICT.2015.15.
S. Mishra, S. Jain, C. Rai, and N. Gandhi, “Security challenges in semantic web of things,” 2019, doi: 10.1007/978-3-030-16681-6_16.
J. Reutter, A. Soto, and D. Vrgoč, “Recursion in SPARQL,” Semant. Web, 2021, doi: 10.3233/SW 200401.
P. Ochieng, “PAROT: Translating natural language to SPARQL,” Expert Syst. with Appl. X, 2020, doi: 10.1016/j.eswax.2020.100024.
J. Potoniec, D. Wiśniewski, A. Ławrynowicz, and C. M. Keet, “Dataset of ontology competency questions to
SPARQL-OWL queries translations,” Data Br., 2020, doi: 10.1016/j.dib.2019.105098.
Y. Chen, M. M. Kokar, and J. J. Moskal, “SPARQL Query Generator (SQG),” J. Data Semant., 2021, doi: 10.1007/s13740-021-00133-y.
W. E. Zhang, Q. Z. Sheng, Y. Qin, K. Taylor, and L. Yao, “Learning-based SPARQL query performance modeling and prediction,” World Wide Web, 2018, doi: 10.1007/s11280-017-0498-1.
F. Michel, C. F. Zucker, O. Gargominy, and F. Gandon, “Integration of web APIs and linked data using SPARQL micro-services-Application to biodiversity use cases,” Inf., 2018, doi: 10.3390/info9120310.
R. Valencia-García, F. García-Sánchez, D. Castellanos Nieves, J. T. Fernández-Breis, and A. Toval, “Exploitation of social semantic technology for software development team configuration,” IET Softw., 2010, doi: 10.1049/iet-sen.2010.0043.
X. Ji, S. A. Chun, and J. Geller, “Social infobuttons: Integrating open health data with social data using semantic technology,” 2013, doi: 10.1145/2484712.2484718.
P. Singto and A. Mingkhwan, “Semantic Searching IT Careers Concepts Based on Ontology,” J. Adv. Manag. Sci., 2013, doi: 10.12720/joams.1.1.102-106.
M. Mochol, H. Wache, and L. Nixon, “Improving the accuracy of job search with semantic techniques,” 2007, doi: 10.1007/978-3-540-72035-5_23.
T. Schweizer and B. Geer, “Gravsearch: Transforming SPARQL to query humanities data,” Semant. Web, 2021, doi: 10.3233/SW-200386.
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