期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：11
DOI：10.14569/IJACSA.2016.071132
出版社：Science and Information Society (SAI)
摘要：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%.
关键词：thesai; IJACSA Volume 7 Issue 11; issue tracking; ontology; similarity computation; vector space model
