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Improving Service Processes and The Library Quality Service with Data Mining Methods

Yıl 2018, Cilt: 9 Sayı: 33, 91 - 100, 01.07.2018
https://doi.org/10.5824/1309-1581.2018.3.005.x

Öz

In this digital age, businesses that collect consumer information provide better service to its customers or new market areas in the name of consumer information from the open mining, artificial intelligence techniques, methods and algorithms in conjunction with data mining are used in order to be able to get the results of these operations.Data mining methods in an intensive competition environment in the service-producing process, are being used effectively. For customer relations in the context of these techniques in improving library processes and in improving the quality of service data mining method is utilized.The data aim-based of this study was to set a specific time range of the data that is received from a public University. Study of the library data in question required data mining methods of clustering and the apriori algorithm.As a result, the library data are implemented on data mining algorithms in the library with the given service processes and improvement of the quality of these services being the defining periodic changing of profile reader to reader demands and determined display and readers library interactions. Subsequent studies based on data from different universities library may lead too to different research, comparisons, and therefore different results. At the same time, the results of repeated studies for the readers of different library can be evaluated. İn similar studies, the amount of data and the range of time can be effective on the results too.

Kaynakça

  • Akpınar, H. Veri Tabanlarında Bilgi Keşfi ve Veri Madenciliği, İ.Ü. İşletme Fakültesi Dergisi. C:29, 1- 22 ss; 2000.
  • Argüden, Y., Erşahin, B. Veri Madenciliği: Veriden Bilgiye, Masraftan Değere,1.Basım, ARGE Danışmanlık Yayınları, İstanbul; 2008.
  • Berry, M.J.A ve Linoff, G.S, Data Mining Techniques: For Marketing, Sales and Customer Relationship Management, New York: John Wiley & Sons Inc; 2004.
  • Chapman, P. CRISP-DM 1.0 Step-by-step data mining guide, SPSS Inc; 2000.
  • Erpolat Semra, Otomobil Yetkili Servislerinde Birliktelik Kurallarının Belirlenmesinde Apriori ve FP- Growth Algoritmalarının Karşılaştırılması, Sosyal Bilimler Dergisi(C12S2), Anadolu Üniv; 2012.
  • Özkan, Y. Veri Madenciliği Yöntemleri, 1. Basım, Papatya Yayınları; 2008.
  • Surendiran R., Rajan.K.P. ve Sathish K.M., Study on the Customer Targeting Using Association Rule Mining. Surendiran et. al., (IJCSE) International Journal on Computer Science and Engineering, Madurai, India, Vol. 02, No. 07, 2010, 2483-2484, ISSN : 0975-3397; 2010.
  • Vishal S., Nikita J. ve Sharad V., (). Efficient Use of Apriori Algorithm for Accesing Supermarket Database. IT and Business Intelligence. Proceedings of 2nd international Conference on IT & Business Intelligence (ITBI-10), India, Technically Sponsored by IEEE CIS ISBN No: 978-81- 7446-900-7; 2010. Library Floor

Improving Service Processes and The Library Quality Service with Data Mining Methods

Yıl 2018, Cilt: 9 Sayı: 33, 91 - 100, 01.07.2018
https://doi.org/10.5824/1309-1581.2018.3.005.x

Öz

In this digital age, businesses that collect consumer information provide better service to its customers or new market areas in the name of consumer information from the open mining, artificial intelligence techniques, methods and algorithms in conjunction with data mining are used in order to be able to get the results of these operations.Data mining methods in an intensive competition environment in the service-producing process, are being used effectively. For customer relations in the context of these techniques in improving library processes and in improving the quality of service data mining method is utilized.The data aim-based of this study was to set a specific time range of the data that is received from a public University. Study of the library data in question required data mining methods of clustering and the apriori algorithm.As a result, the library data are implemented on data mining algorithms in the library with the given service processes and improvement of the quality of these services being the defining periodic changing of profile reader to reader demands and determined display and readers library interactions. Subsequent studies based on data from different universities library may lead too to different research, comparisons, and therefore different results. At the same time, the results of repeated studies for the readers of different library can be evaluated. İn similar studies, the amount of data and the range of time can be effective on the results too.

Kaynakça

  • Akpınar, H. Veri Tabanlarında Bilgi Keşfi ve Veri Madenciliği, İ.Ü. İşletme Fakültesi Dergisi. C:29, 1- 22 ss; 2000.
  • Argüden, Y., Erşahin, B. Veri Madenciliği: Veriden Bilgiye, Masraftan Değere,1.Basım, ARGE Danışmanlık Yayınları, İstanbul; 2008.
  • Berry, M.J.A ve Linoff, G.S, Data Mining Techniques: For Marketing, Sales and Customer Relationship Management, New York: John Wiley & Sons Inc; 2004.
  • Chapman, P. CRISP-DM 1.0 Step-by-step data mining guide, SPSS Inc; 2000.
  • Erpolat Semra, Otomobil Yetkili Servislerinde Birliktelik Kurallarının Belirlenmesinde Apriori ve FP- Growth Algoritmalarının Karşılaştırılması, Sosyal Bilimler Dergisi(C12S2), Anadolu Üniv; 2012.
  • Özkan, Y. Veri Madenciliği Yöntemleri, 1. Basım, Papatya Yayınları; 2008.
  • Surendiran R., Rajan.K.P. ve Sathish K.M., Study on the Customer Targeting Using Association Rule Mining. Surendiran et. al., (IJCSE) International Journal on Computer Science and Engineering, Madurai, India, Vol. 02, No. 07, 2010, 2483-2484, ISSN : 0975-3397; 2010.
  • Vishal S., Nikita J. ve Sharad V., (). Efficient Use of Apriori Algorithm for Accesing Supermarket Database. IT and Business Intelligence. Proceedings of 2nd international Conference on IT & Business Intelligence (ITBI-10), India, Technically Sponsored by IEEE CIS ISBN No: 978-81- 7446-900-7; 2010. Library Floor
Toplam 8 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Research Article
Yazarlar

Yüksel Yurtay

Özgür Çiftçi Bu kişi benim

Eyüp Akçetin Bu kişi benim

Yayımlanma Tarihi 1 Temmuz 2018
Gönderilme Tarihi 1 Temmuz 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 9 Sayı: 33

Kaynak Göster

APA Yurtay, Y., Çiftçi, Ö., & Akçetin, E. (2018). Improving Service Processes and The Library Quality Service with Data Mining Methods. AJIT-E: Academic Journal of Information Technology, 9(33), 91-100. https://doi.org/10.5824/1309-1581.2018.3.005.x