Zinātniskās darbības atbalsta sistēma
Latviešu English

Publikācija: Temporal Data Mining for Identifying Customer Behaviour Patterns

Publikācijas veids Citas publikācijas konferenču (arī vietējo) ziņojumu izdevumos
Pamatdarbībai piesaistītais finansējums Nav zināms
Aizstāvēšana: ,
Publikācijas valoda English (en)
Nosaukums oriģinālvalodā Temporal Data Mining for Identifying Customer Behaviour Patterns
Pētniecības nozare 1. Dabaszinātnes
Pētniecības apakšnozare 1.2. Datorzinātne un informātika
Autori Jurijs Čižovs
Tatjana Zmanovska
Arkādijs Borisovs
Atslēgas vārdi Temporal Data Mining (DM), Multi-dimensional Time Series, Customer Behavior Pattern, Cluster Analysis
Anotācija This paper addresses the application of Data Mining technologies in the task of price formation and adjustment for the existing manufacturing plant through studying customer behaviour. The problem of fine price adjustment is especially topical for medium-size and large manufacturing plants. The research is aimed at developing a technique providing a validated recommendation or decision evaluation in the task of price adjustment. The introduced concept of sales volume behaviour profile is based on customer behaviour analysis. A sys-tem to frame and process multidimensional time-series is proposed and imple-mented. A practical result of the study is a software tool enabling the manager to obtain the prediction of the changes in sales volumes for the target decision using their behaviour profiles.
Atsauce Čižovs, J., Zmanovska, T., Borisovs, A. Temporal Data Mining for Identifying Customer Behaviour Patterns. No: Advances in Data Mining in Marketing : 9th Industrial Conference ICDM 2009: Workshop Proceedings DMM 2009, Vācija, Leipzig, 20.-22. jūlijs, 2009. Leipzig: IBaI Publishing, 2009, 22.-32.lpp. ISBN 978-3-940501-07-3.
ID 5556