@Article{cmes.2021.013026,
AUTHOR = {Mohammed Lafi, Bilal Hawashin, Shadi AlZu’ bi},
TITLE = {Eliciting Requirements from Stakeholders’ Responses Using Natural Language Processing},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {127},
YEAR = {2021},
NUMBER = {1},
PAGES = {99--116},
URL = {http://www.techscience.com/CMES/v127n1/41944},
ISSN = {1526-1506},
ABSTRACT = {Most software systems have different stakeholders with a variety of concerns. The process of collecting requirements
from a large number of stakeholders is vital but challenging. We propose an efficient, automatic approach to
collecting requirements from different stakeholders’ responses to a specific question. We use natural language
processing techniques to get the stakeholder response that represents most other stakeholders’ responses. This study
improves existing practices in three ways: Firstly, it reduces the human effort needed to collect the requirements;
secondly, it reduces the time required to carry out this task with a large number of stakeholders; thirdly, it underlines
the importance of using of data mining techniques in various software engineering steps. Our approach uses
tokenization, stop word removal, and word lemmatization to create a list of frequently accruing words. It then
creates a similarity matrix to calculate the score value for each response and selects the answer with the highest
score. Our experiments show that using this approach significantly reduces the time and effort needed to collect
requirements and does so with a sufficient degree of accuracy.},
DOI = {10.32604/cmes.2021.013026}
}