The cloud paradigm has become increasingly attractive throughout the recent years due to its both technical and economic foreseen impact. Therefore, researchers’ and practitioners’ attention has been drawn to enhancing the technological characteristics of cloud services, such as performance, scalability or security. However, the topic of identifying and understanding cloud consumers’ real needs has largely been ignored. Existing requirements elicitation methods are not appropriate for the cloud computing domain, where consumers are highly heterogeneous and geographically distributed, have frequent change requests and expect services to be delivered at a fast pace. In this paper, we introduce a new approach to requirements elicitation for cloud services, which utilizes consumers’ advanced search queries for services to infer requirements that can lead to new cloud solutions. For this, starting from the queries, we build fuzzy Galois lattices that can be used by public cloud providers to analyze market needs and trends, as well as optimum solutions for satisfying the largest populations possible with a minimum set of features implemented. This new approach complements the existing requirements elicitation techniques in that it is a dedicated cloud method which operates with data that already exists, without entailing the active participation of consumers and requirements specialists.
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