Prioritization of software development demands with text mining techniques

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dc.authoridTUNALI, Volkan/0000-0002-2735-7996en_US
dc.contributor.authorTekin, Murat Can
dc.contributor.authorTunalı, Volkan
dc.date.accessioned2024-07-12T21:37:57Z
dc.date.available2024-07-12T21:37:57Z
dc.date.issued2019en_US
dc.department[Belirlenecek]en_US
dc.description.abstractIn corporations, software issues and software change demands are forwarded to the Information Technology (IT) unit via a demand management system. The priority information in this system has critical importance to the IT unit. However, the priority decision that is left to the individuals who create the demand records may not always be realistic. For instance, a non-critical and low-priority demand may be created with the highest priority, and this may lead to faulty planning and eventually to customer dissatisfaction. In this work, internal customer demands were classified using text mining techniques and their priorities were predicted. The system was trained and tested with the records extracted from the demand management system of a corporation. After cleaning and preprocessing the raw textual demand data, TF-IDF (Term Frequency - Inverse Document Frequency) weighting scheme was used when creating the document-term matrix. Several classification algorithms were tested on the data set generated, and the highest performance was obtained by Sequential Minimal Optimization algorithm with 54.1% F-Score. In addition, on the dataset made balanced with oversampling technique, the highest performance was achieved by Random Forest algorithm with 74.5% F-Score.en_US
dc.identifier.doi10.5505/pajes.2019.47827
dc.identifier.endpage620en_US
dc.identifier.issn1300-7009
dc.identifier.issn2147-5881
dc.identifier.issue5en_US
dc.identifier.startpage615en_US
dc.identifier.trdizinid347721en_US
dc.identifier.urihttps://doi.org/10.5505/pajes.2019.47827
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/347721
dc.identifier.urihttps://hdl.handle.net/20.500.12415/6991
dc.identifier.volume25en_US
dc.identifier.wosWOS:000490929500013en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakTR-Dizin
dc.language.isotren_US
dc.publisherPamukkale Univen_US
dc.relation.ispartofPamukkale University Journal of Engineering Sciences-Pamukkale Universitesi Muhendislik Bilimleri Dergisien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKY04333
dc.subjectSoftware Engineeringen_US
dc.subjectDemand Prioritizationen_US
dc.subjectMachine Learningen_US
dc.subjectText Classificationen_US
dc.subjectRandom Foresten_US
dc.titlePrioritization of software development demands with text mining techniquesen_US
dc.typeArticle
dspace.entity.typePublication

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