文章基本信息

标题：Web App for Dynamic Pricing Modeling in Automotive Applications and Data Mining Analytics
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作者：AlessanMassaro ; Angelo Galiano ; Giacomo Fanelli 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2018
卷号：9
期号：1
页码：4-9
出版社：TechScience Publications
摘要：In this paper the authors propose a web applicationoriented on business to business (B2B) and internetautomotive marketing. The study case is related to anindustrial project concerning tires recognition application andreal time comparison of prices of competitors. By means of asmartphone camera able to identify and classify car plates, thesystem provides different associations of compatible tires for aspecific car model and the best prices. The frontend system isbased on Optical Character Recognition (OCR) method andthe backend works on automatic extraction of competitorprices from different databases and from internet network.The dynamic pricing is due to the best price choice related toperiod of car plate recognition. The price choice is supportedby data mining processing performed by a k-Meansworkflow. The paper summarizes the results of a researchindustrial project. The used approaches could be used fordifferent automotive applications involving market of differentcar parts.
关键词：Web Application; Mobile Marketing; OCR; Tires;detection; Dynamic Pricing; Data Mining; K-Means.