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DOI: 10.14569/IJACSA.2016.071132
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Issue Tracking System based on Ontology and Semantic Similarity Computation

Author 1: Habes Alkhraisat

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 11, 2016.

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Abstract: A computer program is never truly finished; changes are a constant feature of computer program development, there are always something need to be added, redone, or fixed. Therefore, issue-tracking systems are widely used on the system development to keep track of reported issues. This paper proposes a new architecture for automated issue tracking system based on ontology and semantic similarity measure. The proposed architecture integrates several natural languages techniques including vector space model, domain ontology, term-weighting, cosine similarity measure, and synonyms for semantic expansion. The proposed system searches for similar issue templates, which are characteristic of certain fields, and identifies similar issues in an automated way, possible experts and responses are extracted finally. The experimental results demonstrated the accuracy of the new architecture, the experiment result indicates that the accuracy reaches to 94%.

Keywords: issue tracking; ontology; similarity computation; vector space model

Habes Alkhraisat, “Issue Tracking System based on Ontology and Semantic Similarity Computation” International Journal of Advanced Computer Science and Applications(IJACSA), 7(11), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071132

@article{Alkhraisat2016,
title = {Issue Tracking System based on Ontology and Semantic Similarity Computation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071132},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071132},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {11},
author = {Habes Alkhraisat}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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