Classification of product backlog itams in agile software development: a deep learning-based approach (Record no. 18679)

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control field 20230117150730.0
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fixed length control field 230116b xxu||||| |||| 00| 0 eng d
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Original cataloging agency AIKTC-KRRC
Transcribing agency AIKTC-KRRC
100 ## - MAIN ENTRY--PERSONAL NAME
9 (RLIN) 19706
Author Banujan, Kuhaneswaran
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Title Classification of product backlog itams in agile software development: a deep learning-based approach
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Volume, Issue number Vol,18(3), Sep
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Place of publication, distribution, etc. Hyderabad
Name of publisher, distributor, etc. IUP Publications
Year 2022
300 ## - PHYSICAL DESCRIPTION
Pagination 7-26p
520 ## - SUMMARY, ETC.
Summary, etc. Agile software development (ASD) is an iterative mehod project management and software development that enables teams provide customar value more quickly with fewer complications. product backlog items (PBI) are prioritized list to be -implemented ASD requirements prior to beginning sprinting in the ASD, one of the most crucial duties the classification of PBI using machine learning and deep learning methods, the, authors sought to categorize the PBI into spikes,foundational stories,and user storises.they initially gathered data from numerous software development initiatives and web sources. each pbi as classified manually as spikes, foundational stories and preprocessed to remove superfluous text content.using the TF, IDF and GLO Ve techniques, the preprocessed PBI were then embedded with words.ANN and LSTM were used to classife the PBIs. the paper models combinations of TF, IDF+ANN, and GLO VE+LSTM. with an accuracy of 92.4%, the GLO Ve+LSTM model surpassed other deployed models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 4619
Topical term or geographic name entry element EXTC Engineering
700 ## - ADDED ENTRY--PERSONAL NAME
9 (RLIN) 19707
Co-Author Ravi Kumar, Nirubikaa
773 0# - HOST ITEM ENTRY
International Standard Serial Number 0973-2896
Title IUP journal of information technology
Place, publisher, and date of publication Hyderabad IUP Publications
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Koha item type Articles Abstract Database
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          School of Engineering & Technology School of Engineering & Technology Archieval Section 2023-01-16 2023-0122 2023-01-16 2023-01-16 Articles Abstract Database
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