GENERIC ARCHITECTURE FOR INCOORPORATING CLUSTERING INTO E-COMMERCE APPLICATIONS

Anastasios Savvopoulos, Maria Virvou

2009

Abstract

Today product recommending applications use many techniques in order to achieve personalization. These techniques may prove successful but lack in portability. This means that it is very difficult to apply the same architecture and techniques that have been used on one system to a totally different one. In this paper we propose a generic architecture that can be used to achieve personalization to a product recommending system. The main advantage of this architecture is that every system can use it, even if it is built on php, asp.net or a different web technology. In this paper we present a case study that we applied this architecture. This case study proves the independency of our architecture and that it can be applied easily to any kind of remote recommending system.

References

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Paper Citation


in Harvard Style

Savvopoulos A. and Virvou M. (2009). GENERIC ARCHITECTURE FOR INCOORPORATING CLUSTERING INTO E-COMMERCE APPLICATIONS . In Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8111-81-4, pages 427-430. DOI: 10.5220/0001840304270430


in Bibtex Style

@conference{webist09,
author={Anastasios Savvopoulos and Maria Virvou},
title={GENERIC ARCHITECTURE FOR INCOORPORATING CLUSTERING INTO E-COMMERCE APPLICATIONS},
booktitle={Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2009},
pages={427-430},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001840304270430},
isbn={978-989-8111-81-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - GENERIC ARCHITECTURE FOR INCOORPORATING CLUSTERING INTO E-COMMERCE APPLICATIONS
SN - 978-989-8111-81-4
AU - Savvopoulos A.
AU - Virvou M.
PY - 2009
SP - 427
EP - 430
DO - 10.5220/0001840304270430