Research and application of time series algorithms in centralized purchasing data

Yun Bai, Suling Jia, Xixi Li

Research output: Contribution to conferencePaperpeer-review

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Abstract

Based on the online transaction data of COSCO group's centralized procurement platform, this paper studies the clustering method of time series type data. The different methods of similarity calculation, different clustering methods with different K values are analysed, and the best clustering method suitable for centralized purchasing data is determined. The company list under the corresponding cluster is obtained. The time series motif discovery algorithm is used to model the centroid of each cluster. Through ARIMA method, we also made 12 periods of prediction for the centroid of each category. This paper constructs a matrix of "Customer Lifecycle Theory - Five Elements of Marketing ", and puts forward corresponding marketing suggestions for customers at different life cycle stages.
Original languageEnglish
Number of pages7
Publication statusAccepted/In press - 1 Nov 2019
EventThe 14th Conference on Industrial Management - Hangzhou, China
Duration: 12 Sep 201814 Sep 2018

Conference

ConferenceThe 14th Conference on Industrial Management
Country/TerritoryChina
CityHangzhou
Period12/09/1814/09/18

Keywords

  • cs.AI

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