Quantitative evaluation of Clusterings for marketing applications: A web portal case study

• Type: Chapter or Part of a Book
• Date: 2007

Authors

Carmen Rebelo (Author) Other; Pedro Quelhas Brito (Author) FEP; Carlos Soares (Author) FEP; Alipio Jorge (Author) FEP; Rui Brandao (Author) Other

Book

Title: Progress in Artificial Intelligence

Pages: 437-448

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-004-EFJ

DOI: 10.1007/978-3-540-77002-2_37

Abstract (EN): The potential value of a market segmentation for a company is usually assessed in terms of six criteria: identifiability, substantiality, accessibility, responsiveness, stability and actionability. These are widely accepted as essential criteria, but they are difficult to quantify. Quantification is particularly important in early stages of the segmentation process, especially when automatic clustering methods are employed. With such methods it is easy to produce a large number of segmentations but only the most interesting ones should be selected for further analysis. In this paper, we address the problem of how to quantify the value of a segmentation according to the criteria above. We propose several measures and test them on a case study, consisting of a segmentation of portal users.

Language: English

Type (Professor's evaluation): Scientific

Notes: Part of the Lecture Notes in Computer Science book series (LNCS, volume 4874) Print ISBN 978-3-540-77000-8

No. of pages: 12