The new HYREC: a new hybrid product recommender system

Authors:
Paul Fomenky;Zharro Webb;Yenumula Reddy
Affiliations:
Grambling State University, Grambling, LA;Grambling State University, Grambling, LA;Grambling State University, Grambling, LA
Venue:
ASC '07 Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing
Year:
2007

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Abstract

Ecommerce has become ubiquitous as much business is done online nowadays. Some of the more popular such sites include EBay, Amazon and TigerDirect. Product recommendation has become a very important feature of ecommerce as it helps store owners maximize their sales. Over the years, product recommendation has been achieved using a number of techniques. Two of the most popular product recommendation methods are Automated Collaborative Filtering (ACF) and the Case Based Reasoning (CBR) systems. The goal of the research explained below was to handle the sequencing problem that arises because of the usage of such a method. The New HYREC proposes ameliorations to the HYREC product recommender system [1].