Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Introduction Read chapter Read first chapter

2014 | OriginalPaper | Chapter

10. Overview on Cluster Analysis

Authors : Kweku-Muata Osei-Bryson, Sergey Samoilenko

Published in: Advances in Research Methods for Information Systems Research

Publisher: Springer US

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This chapter provides an overview of cluster analysis. Its main purpose is to introduce the reader to the major concepts underlying this data mining (DM) technique, particularly those that are relevant to the chapter that involves the use of this technique. It also provides an illustrative example of cluster analysis.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Reexamining the Impact of Information Technology Investments on Productivity Using Regression Tree- and MARS-Based Analyses
next chapter Overview on Data Envelopment Analysis
Literature
Aggarwal CC, Yu PS (2001) Outlier detection for high dimensional data. In: Proceedings of the 2001 ACM SIGMOD international conference on management of data, pp 37–46
Ankerst M, Breunig M, Kriegel H-P, Sander J (1999) OPTICS: ordering points to identify the clustering structure. In: Proceedings of ACM SIGMOD’99 international conference on the management of data, Philadelphia, PA, 1999, pp 49–60
Balijepally V, Mangalaraj G, Iyengar K (2011) Are we wielding this hammer correctly? A reflective review of the application of cluster analysis in information systems research. J Assoc Inf Syst 12(5):375–413
Balijepally V (2006) Application of cluster analysis in information systems research: a review. A & M University, Prairie View
Bittman A, Gelbrand R (2009) Visualization of multi-algorithm clustering for better economic decisions—the case of car pricing. Decis Support Syst 47(1):42–50CrossRef
Bezdek J (1981) Pattern recognition with fuzzy objective function algorithms. Plenum Press, New YorkCrossRef
Bock H (1996) Probability models in partitional cluster analysis. Comput Stat Data Anal 23:5–28CrossRef
Chen S-C, Ching R, Lin Y-S (2004) An extended study of the k-means algorithm for data clustering and its applications. J Oper Res Soc 55:976–987CrossRef
Dave R (1992) Generalized fuzzy C-shells clustering and detection of circular and elliptic boundaries. Pattern Recogn 25:713–722
Dubes R (1983) Cluster analysis and related issues. In: Chen C, Pau L, Wang P (eds) Handbook of pattern recognition and computer vision. World Scientific Publishing Co. Inc., River Edge, pp 3–32
Dunn J (1974) Well separated clusters and optimal fuzzy partitions. J Cybern 4:95–104CrossRef
Gordon A (1999) Classification. Chapman & Hall, New York
Huang J, Ng M, Rong H, Li Z (2005) Automated variable weighting in k-means type clustering. IEEE Trans Pattern Anal Mach Intell 27(5):657–668CrossRef
Jain A, Dubes R (1988) Algorithms for clustering data. Prentice-Hall advanced reference series. Prentice-Hall Inc., Upper Saddle River
Jain A, Murty M, Flynn P (1999) Data clustering: a review. ACM Comput Surv 31(3):264–323CrossRef
Kimani S, Lodi S, Catarci T, Santucci G, Sartori Vidamine C (2004) A visual data mining environment. J Visual Lang Comput 15:37–67CrossRef
Mathers W, Choi D (2004) Cluster analysis of patients with ocular surface disease blepharitis, and dry eye. Arch. Ophthalmol. 122:1700–1704CrossRef
Mc Queen J (1967) Some methods for classification and analysis of multivariate observations. In: Lecam LM, Neyman J (eds) Proceedings of the 5th Berkeley symposium on mathematical statistics and probability. California Press, Berkeley, pp 281–297
Murtagh F (1983) A survey of recent advances in hierarchical clustering algorithms which use cluster centers. Comput J 26:354–359CrossRef
Okazaki S (2006) What do we know about mobile internet adopters? A cluster analysis. Inf Manage 43(2):127–141CrossRef
Osei-Bryson K-M (2005) Assessing cluster quality using multiple measures. The next wave in computing, optimization, and decision technologies, pp 371–384
Rai A, Tang X, Brown P, Keil M (2006) Assimilation patterns in the use of electronic procurement innovations: a cluster analysis. Inf Manage 43(3):336–349CrossRef
Ramze Rezaee M, Lelieveldt B, Reiber J (1998) A new cluster validity index for the fuzzy c-mean. Pattern Recogn Lett 19:237–246CrossRef
Samoilenko S, Osei-Bryson K-M (2010) Determining sources of relative inefficiency in heterogeneous samples: methodology using cluster analysis, DEA and neural networks. Eur J Oper Res 206(2):479–487CrossRef
Tibshirani R, Walther G (2005) Cluster validation by prediction strength. J Comput Graph Stat 14(5):11–28
Wallace L, Keil M, Rai A (2004) Understanding software project risk: a cluster analysis. Inf Manage 42:115–155CrossRef
Ward J (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58:236–244CrossRef
Metadata
Title
Overview on Cluster Analysis
Authors
Kweku-Muata Osei-Bryson
Sergey Samoilenko
Copyright Year
2014
Publisher
Springer US
Book
Advances in Research Methods for Information Systems Research

Print ISBN: 978-1-4614-9462-1

Electronic ISBN: 978-1-4614-9463-8

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-1-4614-9463-8_10

Premium Partner

    Image Credits