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dc.contributor.authorArslan H.
dc.contributor.authorKaynar O.
dc.contributor.authorŞahin S.
dc.date.accessioned2019-07-27T12:10:23Z
dc.date.accessioned2019-07-28T09:32:53Z
dc.date.available2019-07-27T12:10:23Z
dc.date.available2019-07-28T09:32:53Z
dc.date.issued2019
dc.identifier.isbn9781538668788
dc.identifier.urihttps://dx.doi.org/10.1109/IDAP.2018.8620734
dc.identifier.urihttps://hdl.handle.net/20.500.12418/5646
dc.description2018 International Conference on Artificial Intelligence and Data Processing, IDAP 2018 -- 28 September 2018 through 30 September 2018 --en_US
dc.description.abstractCorporate firms that aim to be permanent in the long term should not lose existing customers and need to win new customers. The increase in the number of firms offering similar services also increases the alternatives for customers. For this reason, there is no guarantee of long-term working with a customer. It has become compulsory to manage customer demands for companies that are in a highly competitive environment. In order to be able to sustain customer loyalty in the long term, they should better recognize them and provide quick returns to their demands. Firms are using help desk applications to manage these demands. Help desk applications are systems that aim to provide information and support to customers or end users about firms' services. In this study, customer demands were analyzed using text mining and machine learning algorithms and classified according to organizational workflow. The data sets used in the study and customer demands were obtained from help desk belonging to Detaysoft which offers live support to over 300 customers. © 2018 IEEE.en_US
dc.language.isoturen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.isversionof10.1109/IDAP.2018.8620734en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectbusiness managementen_US
dc.subjectcustomer demandsen_US
dc.subjecthelpdesken_US
dc.titleClassification of Customer Demands by Organizational Workflows [Müsteri Taleplerinin Organizasyonel Is Akislarina Uygun Siniflandirilmasi]en_US
dc.typeconferenceObjecten_US
dc.relation.journal2018 International Conference on Artificial Intelligence and Data Processing, IDAP 2018en_US
dc.contributor.departmentArslan, H., Bilgisayar Mühendisli?i, Cumhuriyet Üniversitesi, Sivas, Turkey -- Kaynar, O., Yönetim Bilişim Sistemleri, Cumhuriyet Üniversitesi, Sivas, Turkey -- Şahin, S., Sosyal Bilimler Enstitüsü, Cumhuriyet Üniversitesi, Sivas, Turkeyen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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