Machine learning based success prediction for crowdsourcing software projects-Reference-Cited by-同舟云学术

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Machine learning based success prediction for crowdsourcing software projects

Published:2021-08 Issue: Volume:178 Page:110965
ISSN:0164-1212
Container-title:Journal of Systems and Software
language:en
Short-container-title:Journal of Systems and Software

Author:

Illahi Inam,Liu Hui,Umer Qasim,Niu Nan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference38 articles.

1. Yake! collection-independent automatic keyword extractor;Campos,2018

2. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods;Cristianini,2000

3. Dynamics of Software Development Crowdsourcing;Dubey,2016

4. The Dos and Don’ts of Crowdsourcing Software Development, Vol. 8939;Fitzgerald,2015

5. Competition-aware task routing for contest based crowdsourced software development;Fu,2017

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1. Machine learning and deep learning in project analytics: methods, applications and research trends;Production Planning & Control;2024-03-11

2. Cost Adjustment for Software Crowdsourcing Tasks Using Ensemble Effort Estimation and Topic Modeling;Arabian Journal for Science and Engineering;2024-02-27

3. Success Prediction of Crowdsourced Projects for Competitive Crowdsourced Software Development;Applied Sciences;2024-01-05

4. Metrics for Project Management Methodologies Elicitation;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2023-06-30

5. How publications and patents are contributing to the development of municipal solid waste management: Viewing the UN Sustainable Development Goals as ground zero;Journal of Environmental Management;2023-01

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