標題: Merging anomalous data usage in wireless mobile telecommunications: Business analytics with a strategy-focused data-driven approach for sustainability
作者: Chen, Yi-Ting
Sun, Edward W.
Lin, Yi-Bing
資訊工程學系
Department of Computer Science
關鍵字: Analytics;Artificial intelligence;Data mining;Decision support systems;OR in telecommunications;Validation of OR Computations
公開日期: 16-三月-2020
摘要: Mobile internet usage has exploded with the mass popularity of smartphones that offer more convenient and efficient ways of doing anything from watching movies, playing games, and streaming music. Understanding the patterns of data usage is thus essential for strategy-focused data-driven business analytics. However, data usage has several unique stylized facts (such as high dimensionality, heteroscedasticity, and sparsity) due to a great variety of user behaviour. To manage these facts, we propose a novel density-based subspace clustering approach (i.e., a three-stage iterative optimization procedure) for intelligent segmentation of consumer data usage/demand. We discuss the characteristics of the proposed method and illustrate its performance in both simulation with synthetic data and business analytics with real data. In a field experiment of wireless mobile telecommunications for data-driven strategic design and managerial implementation, we show that our method is adequate for business analytics and plausible for sustainability in search of business value. (C) 2019 Published by Elsevier B.V.
URI: http://dx.doi.org/10.1016/j.ejor.2019.02.046
http://hdl.handle.net/11536/153354
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2019.02.046
期刊: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume: 281
Issue: 3
起始頁: 687
結束頁: 705
顯示於類別:期刊論文