Online shopping has been prevalent in our daily life. Profiling users and understanding their browsing behaviors are critical for enhancing shopping experience and maximizing sales revenue. In this paper, based on a one-month dataset recording 2 million users’ 67 million online shopping and browsing logs, we seek to understand how users browse and shop products, and how distinct these behaviors are. We find that there exist dedicate groups of users that prefer certain product categories corresponding to similar demands. Moreover, distinct differences of behaviors exist in categories, where repetitive and targeted browsing are two major prevalent patterns.
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These include Phone & Accessories (MP & AC), PC & Office (PC & OF), Books & CDs (BK & CD), Clothes (CL), House Decorations (DE), Household Appliances (HA), Sports & Health (SP & HE), Gifts & Bags (GI & BA), Cosmetics (CM), Maternity & Child (MA & CH) and Digital Products (DP).
Anderson A, Kumar R, Tomkins A, Vassilvitskii S (2014) The dynamics of repeat consumption. In: International conference on world wide web, pp 419–430
Benson AR, Kumar R, Tomkins A (2016) Modeling user consumption sequences. In: International conference on world wide web. International world wide web conferences steering committee, pp 519–529
Chen M, Ma Y, Song J, Lai CF, Hu B (2016) Smart clothing: connecting human with clouds and big data for sustainable health monitoring. Mobile Networks and Applications 21(5):825–845
Chen M, Hao T, Hwang K, Wang L (2017) Disease prediction by machine learning over big healthcare data. IEEE Access 4:1242–1253
Chen M, Ma Y, Li Y, Wu D, Zhang Y, Youn (2017) Wearable 2.0: enable human-cloud integration in next generation healthcare system. IEEE Communications 55(1):54–61
Chen M, Yang J, Hao Y, Mao S, Hwang K (2017) A 5G cognitive system for healthcare. Big Data and Cognitive Computing 1(1)
eMarketer (2016) Worldwide retail ecommerce sales: emarketer’s updated estimates and forecast through 2019, pp 2–4. http://www.emarketer.com/public_media/docs/eMarketer_eTailWest2016_Worldwide_ECommerce_Report.pdf
Keralapura R, Nucci A, Zhang ZL, Gao L (2010) Profiling users in a 3g network using hourglass co-clustering. In: International conference on mobile computing and networking, MOBICOM 2010, Chicago, Illinois, USA, September. DBLP, vol 49, pp 341–352
Li J, Qiu M, Ming Z, Quan G, Qin X, Gu Z (2012) Online optimization for scheduling preemptable tasks on IaaS cloud systems. J Parallel Distrib Comput 72(5):666–677
Li Y, Chen M (2015) Software-defined Network function virtualization: a survey. IEEE Access 3:2542–2553
Liu CH, Zhang Z, Chen M (2017) Personalized multimedia recommendations by adaptive feedback control frameworks for cloud-integrated cyber physical systems. IEEE Syst J 11(1):106–117
Qiu M, Ming Z, Li J, Gai K, Zong Z (2015) Phase-change memory optimization for green cloud with genetic algorithm. IEEE Trans Comput 64 (12):3528–3540
Qiu M, Sha HM (2009) Cost minimization while satisfying hard/soft timing constraints for heterogeneous embedded systems. ACM Trans Des Autom Electron Syst 14(2):1–30
Tian D, Zhou J, Wang Y, Lu Y (2015) A dynamic and self-adaptive network selection method for multimode communications in heterogeneous vehicular telematics. IEEE Trans Intell Transp Syst 16(6):3033–3049
Tian D, Zhou J, Sheng Z (2017) An adaptive fusion strategy for distributed information estimation over cooperative multi-agent networks. IEEE Trans Inf Theory 99:1–1
Zhang Y (2016) Grorec: a group-centric intelligent recommender system integrating social, mobile and big data technologies. IEEE Trans Serv Comput 9(5):786–795
Zhang Y, Zhang D, Hassan MM, Alamri A, Peng L (2015) CADRE: cloud-assisted drug REcommendation service for online pharmacies. Mobile Networks and Applications 20(3):348–355
Zhang Y, Chen M, Huang D, Wu D, Li Y (2016) iDoctor: personalized and professionalized medical recommendations based on hybrid matrix factorization. Futur Gener Comput Syst 66:30–35
Zheng K, Yang Z, Zhang K, Chatzimisios P (2016) Big data-driven optimization for mobile networks toward 5G. IEEE Netw 30(1):44–51
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Yan, H., Wang, Z., Lin, T. et al. Profiling users by online shopping behaviors. Multimed Tools Appl 77, 21935–21945 (2018). https://doi.org/10.1007/s11042-017-5365-7
- Social network
- User behavior analytics
- Data analysis