Title | ||
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Non-functional Requirements for Machine Learning: Understanding Current Use and Challenges in Industry |
Abstract | ||
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Machine Learning (ML) is an application of Artificial Intelligence (AI) that uses big data to produce complex predictions and decision-making systems, which would be challenging to obtain otherwise. To ensure the success of ML-enabled systems, it is essential to be aware of certain qualities of ML solutions (performance, transparency, fairness), known from a Requirement Engineering (RE) perspectiv... |
Year | DOI | Venue |
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2021 | 10.1109/RE51729.2021.00009 | 2021 IEEE 29th International Requirements Engineering Conference (RE) |
Keywords | DocType | ISSN |
Non-Functional Requirements,NFRs,qualities,Machine Learning,NFR Challenges,Requirements Engineering | Conference | 2332-6441 |
ISBN | Citations | PageRank |
978-1-6654-2856-9 | 2 | 0.49 |
References | Authors | |
0 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Khan Mohammad Habibullah | 1 | 2 | 0.49 |
Jennifer Horkoff | 2 | 888 | 69.90 |