RNN-CNN MODEL: A bi-directional long short-term memory deep learning network for story point estimation
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Marapelli, B, Carie, A and Islam, Sardar M. N 
ORCID: 0000-0001-9451-7390
(2020)
RNN-CNN MODEL: A bi-directional long short-term memory deep learning network for story point estimation.
In: Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA 2020), 25 Nov 2020 - 27 Nov 2020.
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| Item type | Conference or Workshop Item (Paper) |
| URI | https://vuir.vu.edu.au/id/eprint/43579 |
| DOI | 10.1109/CITISIA50690.2020.9371770 |
| Official URL | https://ieeexplore.ieee.org/document/9371770 |
| ISBN | 9781728194370 |
| Subjects | Current > FOR (2020) Classification > 4611 Machine learning Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | agile software development; user story description; feature extraction; feature encoding; BiLSTM |
| Citations in Scopus | 5 - View on Scopus |
| Download/View statistics | View download statistics for this item |
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