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E-commerce businessmodel mining and prediction

Zhou-zhou HE,Zhong-fei ZHANG,Chun-ming CHEN,Zheng-gang WANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 9,   Pages 707-719 doi: 10.1631/FITEE.1500148

Abstract: We study the problem of business model mining and prediction in the e-commerce context. Unlike most existing approaches where this is typically formulated as a regression problem or a time-series prediction problem, we take a different formulation to this problem by noting that these existing approaches fail to consider the potential relationships both among the consumers (consumer influence) and among the shops (competitions or collaborations). Taking this observation into consideration, we propose a new method for e-commerce business model mining and prediction, called EBMM, which combines regression with community analysis. The challenge is that the links in the network are typically not directly observed, which is addressed by applying information diffusion theory through the consumer-shop network. Extensive evaluations using Alibaba Group e-commerce data demonstrate the promise and superiority of EBMM to the state-of-the-art methods in terms of business model mining and prediction.

Keywords： E-commerce     Business model prediction     Consumer influence     Social network     Sales prediction    

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E-commerce businessmodel mining and prediction

Zhou-zhou HE,Zhong-fei ZHANG,Chun-ming CHEN,Zheng-gang WANG

Journal Article