bth.se
Please wait ...
Simple search
Advanced search -
Research publications
Advanced search -
Student theses
Statistics
English
Svenska
Norsk
Jump to content
Change search
Search
Search
Only documents with full text in DiVA
Cite
Export
BibTex
CSL-JSON
CSV 1
CSV 2
CSV 3
CSV 4
CSV 5
CSV all metadata
CSV all metadata version 2
RIS
Mods
MARC-XML
ETDMS
Link to record
Permanent link
https://urn.kb.se/resolve?urn=urn:nbn:se:bth-24945
Direct link
http://bth.diva-portal.org/smash/record.jsf?pid=diva2:1773692
Cite
Citation style
apa
ieee
modern-language-association-8th-edition
vancouver
Other style
apa
ieee
modern-language-association-8th-edition
vancouver
Other style
More styles
Language
de-DE
en-GB
en-US
fi-FI
nn-NO
nn-NB
sv-SE
Other locale
de-DE
en-GB
en-US
fi-FI
nn-NO
nn-NB
sv-SE
Other locale
More languages
Output format
html
text
asciidoc
rtf
html
text
asciidoc
rtf
Create
Close
Classification of User Stories using aNLP and Deep Learning Based Approach
Kandikari, Bhavesh
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2023 (English)
Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE credits
Student thesis
Place, publisher, year, edition, pages
2023.
Keywords [en]
Natural Language Processing, Word Embedding, Requirement Refining, User Story, Deep Learning
National Category
Computer Sciences
Identifiers
URN:
urn:nbn:se:bth-24945
OAI: oai:DiVA.org:bth-24945
DiVA, id:
diva2:1773692
External cooperation
Ericsson Karlskrona
Subject / course
DV2572 Master´s Thesis in Computer Science
Educational program
DVADA Master Qualification Plan in Computer Science
Supervisors
Lavesson, Niklas
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
Examiners
Mendes, Emilia
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Available from:
2023-06-26
Created:
2023-06-22
Last updated:
2023-06-26
Bibliographically approved
Open Access in DiVA
Classification of User Stories using a NLP and Deep Learning Based Approach
(2884 kB)
1040 downloads
File information
File name
FULLTEXT02.pdf
File size
2884 kB
Checksum
SHA-512
61469c3fa066609effbc858f790e62c591624bd3ee8ab947b9fbeed81df6d059db7f97b91105367d27d0c0c066b535dd18a554c3ebf11239c7d4d3ae387125da
Type
fulltext
Mimetype
application/pdf
By organisation
Department of Computer Science
On the subject
Computer Sciences
Search outside of DiVA
Google
Google Scholar
Total: 1041 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available
urn-nbn
Altmetric score
urn-nbn
Total: 98 hits
Cite
Export
BibTex
CSL-JSON
CSV 1
CSV 2
CSV 3
CSV 4
CSV 5
CSV all metadata
CSV all metadata version 2
RIS
Mods
MARC-XML
ETDMS
Link to record
Permanent link
https://urn.kb.se/resolve?urn=urn:nbn:se:bth-24945
Direct link
http://bth.diva-portal.org/smash/record.jsf?pid=diva2:1773692
Cite
Citation style
apa
ieee
modern-language-association-8th-edition
vancouver
Other style
apa
ieee
modern-language-association-8th-edition
vancouver
Other style
More styles
Language
de-DE
en-GB
en-US
fi-FI
nn-NO
nn-NB
sv-SE
Other locale
de-DE
en-GB
en-US
fi-FI
nn-NO
nn-NB
sv-SE
Other locale
More languages
Output format
html
text
asciidoc
rtf
html
text
asciidoc
rtf
Create
Close
v. 2.44.0
|
WCAG
|
BTH Library
|
Publish/Register
|
How to publish/register
|
Diva portal
|
SwePub
|
Uppsök
DiVA
Logotyp