A computational geometry approach to Web personalization

Author

Rigou, Maria ; Sirmakessis, Spiros ; Tsakalidis, Athanasios

Author_Institution

Res. Acad., Comput. Technol. Inst., Patras, Greece

fYear

2004

fDate

6-9 July 2004

Firstpage

377

Lastpage

380

Abstract

In this paper we present an algorithm for efficient personalized clustering. The algorithm combines the orthogonal range search with the k-windows algorithm. It offers a real-time solution for the delivery of personalized services in online shopping environments, since it allows on-line consumers to model their preferences along multiple dimensions, search for product information, and then use the clustered list of products and services retrieved for making their purchase decisions.

Keywords

Internet; computational geometry; data mining; home shopping; information retrieval; Web personalization; clustered product list; clustered services; computational geometry; efficient personalized clustering; k-windows algorithm; multiple dimensions; online shopping; orthogonal range search; personalized services; preferences model; product information; purchase decisions; real-time solution; Clustering algorithms; Computational geometry; Data mining; Educational institutions; Educational technology; Informatics; Information retrieval; Internet; Machine learning algorithms; Recommender systems;

fLanguage

English

Publisher

ieee

Conference_Titel

e-Commerce Technology, 2004. CEC 2004. Proceedings. IEEE International Conference on

Print_ISBN

0-7695-2098-7

Type

conf

DOI

10.1109/ICECT.2004.1319762

Filename

1319762