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Group Recommendation Techniques for Feature Modeling and Configuration

  • arXiv (Cornell University)
  • Cornell University
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Abstract

In large-scale feature models, feature modeling and configuration processes are highly expected to be done by a group of stakeholders. In this context, recommendation techniques can increase the efficiency of feature-model design and find optimal configurations for groups of stakeholders. Existing studies show plenty of issues concerning feature model navigation support, group members' satisfaction, and conflict resolution. This study proposes group recommendation techniques for feature modeling and configuration on the basis of addressing the mentioned issues.

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Publication details

DOI
10.48550/arxiv.2104.06054
OpenAlex
W3156695235
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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