RNN-CNN MODEL: A bi-directional long short-term memory deep learning network for story point estimation

Full text for this resource is not available from the Research Repository.

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.

Dimensions Badge

Altmetric Badge

Item type Conference or Workshop Item (Paper)
URI https://vuir.vu.edu.au/id/eprint/43579
DOI https://doi.org/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 1 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login