HYREC: A Hybrid Recommendation System for E-Commerce

  • Bhanu Prasad
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3620)


Product recommendation is very important in business to customer (B2C) e-commerce. Automated Collaborative Filtering (ACF) is an important approach for product recommendation. However, a major drawback with this approach is that it can’t avoid the “sequence recognition problem”, explained in this paper. Here we present a system that addresses the sequence recognition problem by recording and utilizing the users’ purchase patterns and ratings. The proposed system is a fruitful combination of ACF and Case-Based Reasoning Plan Recognition (CBRPR) methods. The evaluation studies prove that the hybrid system provides better performance when compared to ACF and CBRPR methods used individually.


Recommendation System Acceptance Rate Collaborative Filter Product Recommendation Recommendation Process 
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 2005

Authors and Affiliations

  • Bhanu Prasad
    • 1
  1. 1.Department of Computer and Information SciencesFlorida A&M UniversityTallahasseeUSA

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