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Title:Uporaba metod strojnega učenja za klasifikacijo nalog po prioritetah v IT projektih
Authors:ID Unuchak, Tatyana (Author)
ID Kljajić Borštnar, Mirjana (Author)
ID Unuchak, Yauhen (Author)
Files:URL https://uporabna-informatika.si/ui/article/view/240/206
 
.pdf 620+(Unuchak).pdf (2,25 MB)
MD5: EFB852B9482EB79ED8DCE4562521AD25
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:FOV - Faculty of Organizational Sciences in Kranj
Abstract:Določanje prioritet in razvrščanje nalog še vedno predstavlja izziv pri učinkovitem vodenju projektov. Obstaja veliko klasičnih pristopov za določanje prioritet. Vendar so te tehnike delovno intenzivne, subjektivne in neprilagodljive. V prispevku obravnavamo pristope za samodejno določanje prioritet nalog v IT projektih, ki temeljijo na strojnem učenju. Raziskujemo, kako lahko z uporabo metod strojnega učenja pomagamo projektnim vodjem pri učinkovitejšem razvrščanju nalog v IT projektih. V ta namen smo na množici več kot 1000000 zapisov projektnih nalog razvili klasifikacijski model za samodejno določanje prioritet. Problem, ki smo ga obravnavali, je večrazredni, pri tem je večina primerov, označenih z najvišjo prioriteto, kar predstavlja izziv pri modeliranju kot tudi pri učinkovitosti upravljanja IT projektov. Preskusili smo različne algoritme ter različne pristope, s ciljem izboljšanja rezultatov klasifikacije. Pokazali smo, da je naloge smiselno razvrstiti v manjše skupine prioritet, kar prispeva k večji natančnosti klasifikacijskega modela in preglednosti prioritet nalog, slednje pa lahko olajša upravljanje IT projektov.
Keywords:IT project management, machine learning, task prioritization, multiclass classification, data imbalance
Publication status:Published
Publication version:Version of Record
Publication date:09.01.2025
Year of publishing:2025
Number of pages:str. 3-17
Numbering:Letn. 33, št. 1
PID:20.500.12556/DKUM-94839 New window
UDC:004.8
ISSN on article:1318-1882
COBISS.SI-ID:238610691 New window
DOI:10.31449/upinf.240 New window
Publication date in DKUM:28.08.2025
Views:136
Downloads:11
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Uporabna informatika
Shortened title:Uporab. inform.
Publisher:Slovensko društvo Informatika
ISSN:1318-1882
COBISS.SI-ID:36338688 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Title:Using machine learning methods to classify tasks by priority in ITprojects
Abstract:Prioritizing and classifying tasks remain a challenge in effective project management. There are many classic approaches to prioritization. However, all these techniques are labour intensive, subjective and lack flexibility. In this paper we investigate machine learning based approaches for automatic prioritization of tasks in IT projects. We explore how machine learning methods can be used to help project managers prioritize tasks in IT projects more efficiently. We developed a classification model for automatically determining priorities based on a dataset of over 1,000,000 project task records. The problem we addressed is multi-class, with the majority of cases labelled with the highest priority, which presents a challenge both in modelling and in the efficiency of IT project management. To address these challenges, we explored strategies to enhance classification performance, including reducing the number of priority classes. Our findings demonstrate that simplifying the priority structure improves the model’s accuracy and contributes to more efficient task management in IT projects.
Keywords:vodenje ITprojektov, strojno učenje, določanje prioritet nalog, večrazredna klasifikacija, neuravnoteženost podatkov, neuravnoteženost podatkov


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