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Common Sense Knowledge, Ontology and Text Mining for Implicit Requirements

Emebo, Onyeka and Varde, Aparna S. and Daramola, Olawande (2016) Common Sense Knowledge, Ontology and Text Mining for Implicit Requirements. In: Int'l Conf. Data Mining.

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The ability of a system to meet its requirements is a strong determinant of success. Thus effective requirements specification is crucial. Explicit Requirements are well-defined needs for a system to execute. IMplicit Requirements (IMRs) are assumed needs that a system is expected to fulfill though not elicited during requirements gathering. Studies have shown that a major factor in the failure of software systems is the presence of unhandled IMRs. Since relevance of IMRs is important for efficient system functionality, there are methods developed to aid the identification and management of IMRs. In this paper, we emphasize that Common Sense Knowledge, in the field of Knowledge Representation in AI, would be useful to automatically identify and manage IMRs. This paper is aimed at identifying the sources of IMRs and also proposing an automated support tool for managing IMRs within an organizational context. Since this is found to be a present gap in practice, our work makes a contribution here. We propose a novel approach for identifying and managing IMRs based on combining three core technologies: common sense knowledge, text mining and ontology. We claim that discovery and handling of unknown and non-elicited requirements would reduce risks and costs in software development.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Implicit Requirements, Common Sense Knowledge, Ontology, Text Mining, Requirement Engineering
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Hannah Akinwumi
Date Deposited: 14 Mar 2019 08:36
Last Modified: 14 Mar 2019 08:36

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