Recommendation system based on the clustering of frequent sets

Authors:
Andrei Toma;Radu Constantinescu;Floarea Nastase
Affiliations:
The Economic Informatics Department, Academy of Economic Studies, Bucharest, Romania;The Economic Informatics Department, Academy of Economic Studies, Bucharest, Romania;The Economic Informatics Department, Academy of Economic Studies, Bucharest, Romania
Venue:
WSEAS Transactions on Information Science and Applications
Year:
2009

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Abstract

Generating shopping recommendations has become a classical problem in knowledge engineering with extensive practical applications. In this article we propose a system for the generation of such recommendations based on considering both local and global influences.