Kontaktujte nás | Jazyk: čeština English
dc.title | Toward applying agglomerative hierarchical clustering in improving the software development effort estimation | en |
dc.contributor.author | Vo Van, Hai | |
dc.contributor.author | Ho, Le Thi Kim Nhung | |
dc.contributor.author | Jašek, Roman | |
dc.relation.ispartof | Lecture Notes in Networks and Systems | |
dc.identifier.issn | 2367-3370 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.issn | 2367-3389 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.identifier.isbn | 978-3-03-109069-1 | |
dc.date.issued | 2022 | |
utb.relation.volume | 501 | |
dc.citation.spage | 353 | |
dc.citation.epage | 371 | |
dc.event.title | 11th Computer Science On-line Conference, CSOC 2022 | |
dc.event.location | online | |
dc.event.sdate | 2022-04-26 | |
dc.event.edate | 2022-04-26 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Springer Science and Business Media Deutschland GmbH | |
dc.identifier.doi | 10.1007/978-3-031-09070-7_30 | |
dc.relation.uri | https://link.springer.com/chapter/10.1007/978-3-031-09070-7_30 | |
dc.subject | software effort estimation | en |
dc.subject | function point analysis | en |
dc.subject | hierarchical clustering | en |
dc.subject | machine learning | en |
dc.description.abstract | Background: There are many studies on the effect of data clustering on the effort estimation process. Most of them are on partitioning and density-based clustering, and some use hierarchical clustering but fewer details on the linkage methods. Aim: we concentrate on the aspect of the agglomerative hierarchical clustering algorithm's effectiveness on the accuracy of the effort estimation. Method: We used the agglomerative hierarchical clustering algorithm to group the data into clusters then performed the IFPUG FPA method for effort estimation. The ISBSG dataset was used in this study. The number of clusters is determined using the dendrogram's cut points. Different cut points and linkage methods were employed to cluster the dataset for the comparison. The estimated results of these clusters were compared with the result from the whole dataset without clustering. Result: with the selected number of clusters, results are consistently better than without clustering with all selected evaluation criteria. Conclusion: the accuracy of the effort estimation can be significantly improved when using agglomerative hierarchical clustering. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1011085 | |
utb.identifier.obdid | 43884097 | |
utb.identifier.scopus | 2-s2.0-85135034057 | |
utb.identifier.wok | 000893645700030 | |
utb.source | d-scopus | |
dc.date.accessioned | 2022-08-17T13:17:25Z | |
dc.date.available | 2022-08-17T13:17:25Z | |
dc.description.sponsorship | Faculty of Applied Informatics, Tomas Bata University in Zlin [IGA/CebiaTech/2022/001] | |
utb.ou | Department of Computer and Communication Systems | |
utb.contributor.internalauthor | Vo Van, Hai | |
utb.contributor.internalauthor | Ho, Le Thi Kim Nhung | |
utb.contributor.internalauthor | Jašek, Roman | |
utb.fulltext.sponsorship | This work was supported by the Faculty of Applied Informatics, Tomas Bata University in Zlin, under project IGA/CebiaTech/2022/001. | |
utb.wos.affiliation | [Vo Van Hai; Ho Le Le Le Nhung; Jasek, Roman] Tomas Bata Univ Zlin, Dept Comp & Commun Syst, Nam TGM 5555, Zlin 76001, Czech Republic | |
utb.scopus.affiliation | Department of Computer and Communication Systems, Tomas Bata University in Zlin, Nam. TGM 5555, Zlin, 76001, Czech Republic | |
utb.fulltext.projects | IGA/CebiaTech/2022/001 |
Soubory | Velikost | Formát | Zobrazit |
---|---|---|---|
K tomuto záznamu nejsou připojeny žádné soubory. |