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An Analysis of the State of the Art of Machine Learning for Risk Assessment in Software Projects (S)

AuthID
P-00V-BP0

Author(s)

Sousa, A

Faria, JP

Moreira, JM

Editor(es)

Chang,SK

Tipo de Documento

Proceedings Paper

Year published

2021

Publicado

in The 33rd International Conference on Software Engineering and Knowledge Engineering, SEKE 2021, KSIR Virtual Conference Center, USA, July 1 - July 10, 2021. in SEKE, ISSN: 23259000

Volume: 2021-July, Páginas: 217-222 (5)

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Scopus^®

Dblp^®/pt/publications/view/896704

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Google Scholar^®

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Fontes

Publication Identifiers

DOI: 10.18293/seke2021-097

DBLP: conf/seke/SousaFM21

SCOPUS: 2-s2.0-85114281019

Source Identifiers

ISSN: 23259000

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An Analysis of the State of the Art of Machine Learning for Risk Assessment in Software Projects (S)

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An Analysis of the State of the Art of Machine Learning for Risk Assessment in Software Projects (S)

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