Discovering product counterfeits in online shops: a big data integration challenge
ACM Journal Data and Information Quality, Vol. 5, Aug. 2014
Futher information: http://dl.acm.org/citation.cfm?doid=2667565.2629605
Counterfeit products are illegal imitations or replicas of products offered for sale. Fake products are offered and sold in numerous online shops and auction sites as well as on B2B marketplaces for wholesale trading. Taking actions against counterfeiting in online sales is challenging due to the huge number of involved merchants, websites and product offers. Furthermore, the online business is highly dynamic where product offers as well as websites and merchants change frequently. Identifying likely counterfeits thus requires largely automatic approaches to monitor websites and product offers. The task of discovering online counterfeits thus has the characteristics of a challenging “big data” problem. It involves a large volume of heterogeneous and dynamic data from numerous sources that needs to go through a complex processing pipeline with data acquisition, cleaning, integration and analysis steps.