Abstract
Requirements elicitation is an important task before any development of system repository can be conducted. Typically, traditional methods such as interview, questionnaire and observation are made to gauge the users’ needs. However, the users may not be able to spell out specifically of their need especially if there is no available system to compare resulting to outrageous demands and unrealistic expectations to the repository developer. An alternative approach to gauge the user needs from users’ reviews of the on-the-shelf software may be a good starting point. In this paper we attempt to extract requirements from the users’ independent reviews gathered from the internet using text analytics approach. The keywords are visualized based on its relevance and importance to the user. Then, it is used as a benchmark for the user to alter to their specific repository needs. From the experimental results, it is observed that there are functions that are very much needed by the user and yet there are also functions that are not used at all. Hence, this proposed approach may give insight to the user and developer about the actual needs of the respective system. It is envisaged that such approach can be a guide to the novice user and the developer in order to shorten the time to agree on the development of the repository system.
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Acknowledgements
The authors would like to thank Universiti Teknologi MARA (UiTM), International Islamic University Malaysia (IIUM) and Ministry of Higher Education Malaysia (MOHE) for providing financial support through the MITRA grant (600-IRMI/PERDANA 5/3/MITRA (007/2018)-3) to conduct the work published in this paper.
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Kamaruddin, N., Wahab, A., Bakri, M., Hamiz, M. (2019). Science Lab Repository Requirements Elicitation Based on Text Analytics. In: Berry, M., Yap, B., Mohamed, A., Köppen, M. (eds) Soft Computing in Data Science. SCDS 2019. Communications in Computer and Information Science, vol 1100. Springer, Singapore. https://doi.org/10.1007/978-981-15-0399-3_28
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DOI: https://doi.org/10.1007/978-981-15-0399-3_28
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