Complementary Classification Techniques based Personalized Software Requirements Retrieval with Semantic Ontology and User Feedback

Requirements engineering is an important research area in software engineering. Recent years, with the exponentially growing amount of software developed, it is necessary to elicit appropriate software requirements at an early phase of software development. We provide the complementary classification techniques that combine folksonomy, keyword and facet-based retrieval methods to retrieve software requirements related to users' interests. We add semantic ontology and users' feedback to obtain better software requirements that satisfy users' preferences to enhance software requirements retrieval performance. Finally, we demonstrate the feasibility of the method we proposed in software requirements retrieval using an experiment.