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A Method of Generating Customer’s Profile without History for Providing Recommendation to New Customers in E-Commerce

  • Keonsoo Lee
  • Seungmin Rho
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 179)

Abstract

One of the advantages in E-commerce is that the long tail marketing strategy can be employed. By this, customers can get recommendations about the items, which are rare and specialized to their own tastes. In order to provide this long tail based recommendation service, the service provider needs to have knowledge about the each user’s preference and the similarity among the items which have their own peculiar. If the customer’s purchasing transaction history is provided, his/her preference can be inferred through data mining techniques. But if a customer is new and the purchasing history is empty, it is hard to extract the collect profile for the customer. In this paper, a method of defining the customer’s profile through collective intelligence is proposed. This method can generate profile even if the customer’s personal history does not exist. Therefore a proper recommendation can be provided to newcomers in the service.

Keywords

Recommendation System Target User Collective Intelligence Pareto Principle Behavior History 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Graduation School of Information and CommunicationAjou UniversitySuwonKorea (South)
  2. 2.Division of Information and CommunicationBaekseok UniversityCheonan-CityKorea (South)

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