Solution Architecture for Visitor Segmentation and Recommendation Generation in Real Time

  • Philip Limbeck
  • Josef Schiefer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5183)


With increasing product portfolios of eCommerce companies it is getting harder for their customers to find the products they like best. A solution to this problem is to analyze the customer’s behavior, and recommend products based on ratings. By considering click-stream data, the customer is unburdened with explicitly rating his favored. In this paper, we introduce a system for segmenting visitors and recommending adequate items in real time by using an event-based system called Sense and Respond Infrastructure (SARI) for processing click-stream data. We present the architecture and components for a real-time click-stream analysis which can be easily customized to business needs of domain experts and business users. SARI provides functionality to monitor visitor and customer behavior, respond accordingly and at the same time optimize and adapt customer processes in real time. To illustrate this approach, we introduce a reference implementation, its underlying infrastructure and business scenarios.


Response Event Latent Semantic Analysis Event Service Solution Architecture Rule Service 
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-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Philip Limbeck
    • 1
  • Josef Schiefer
    • 2
  1. 1.Senactive IT Dienstleistungs Gmbh 
  2. 2.Institute for Software Technology and Interactive SystemsVienna University of Technology 

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