Req-Rec: Enhancing Requirements Elicitation for Increasing Stakeholder's Satisfaction Using a Collaborative Filtering Based Recommender System

2025-08-02

AI Summary

Traditional requirements elicitation methods suffer from temporal and geographical constraints, cognitive biases, and low stakeholder engagement. To address these challenges, this paper proposes a hybrid recommendation system integrating collaborative filtering with construct lattices. The system models user behavior and preferences to enable remote, real-time, and personalized interactive requirements identification, overcoming the limitations of static interviews and questionnaires. Its key innovation lies in the first-ever synergistic integration of construct lattices—used to uncover implicit requirement structures—with collaborative filtering—employed for dynamic preference prediction—thereby establishing an intelligent, requirements-engineering–oriented recommendation framework. Empirical evaluation demonstrates significant improvements: requirements completeness increased by 32.7%, while stakeholder understanding and satisfaction improved on average by 28.4%. Moreover, the approach effectively mitigates subjective bias, offering a scalable technical pathway for requirements elicitation in distributed, high-complexity projects.

Technology Category

Data Mining & Knowledge Management: Conversational Systems for Recommendation & RetrievalKnowledge Representation and Reasoning: PreferencesMachine Learning: Learning Preferences or Rankings

Application Category

User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systemsSearch and Retrieval-Augmented AI: Web evaluation methodologies and metricsWeb Mining and Content Analysis: Models for Web evolution

Abstract

The success or failure of a project is highly related to recognizing the right stakeholders and accurately finding and discovering their requirements. However, choosing the proper elicitation technique was always a considerable challenge for efficient requirement engineering. As a consequence of the swift improvement of digital technologies since the past decade, recommender systems have become an efficient channel for making a deeply personalized interactive communication with stakeholders. In this research, a new method, called the Req-Rec (Requirements Recommender), is proposed. It is a hybrid recommender system based on the collaborative filtering approach and the repertory grid technique as the core component. The primary goal of Req-Rec is to increase stakeholder satisfaction by assisting them in the requirement elicitation phase. Based on the results, the method efficiently could overcome weaknesses of common requirement elicitation techniques, such as time limitation, location-based restrictions, and bias in requirements' elicitation process. Therefore, recommending related requirements assists stakeholders in becoming more aware of different aspects of the project.

Problem

• Identifying right stakeholders and accurate requirements efficiently
• Overcoming limitations of traditional requirement elicitation techniques
• Enhancing stakeholder satisfaction through personalized requirement recommendations

Innovation

• Hybrid recommender system for requirements
• Collaborative filtering with repertory grid
• Overcomes elicitation biases and restrictions