Discriminative clustering for market segmentation

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

Discriminative clustering for market segmentation. / Haider, Peter; Chiarandini, Luca; Brefeld, Ulf.
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. New York: Association for Computing Machinery, Inc, 2012. p. 417-425.

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Haider, P, Chiarandini, L & Brefeld, U 2012, Discriminative clustering for market segmentation. in Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. Association for Computing Machinery, Inc, New York, pp. 417-425, 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD-2012, Beijing, China, 12.08.12. https://doi.org/10.1145/2339530.2339600

APA

Haider, P., Chiarandini, L., & Brefeld, U. (2012). Discriminative clustering for market segmentation. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 417-425). Association for Computing Machinery, Inc. https://doi.org/10.1145/2339530.2339600

Vancouver

Haider P, Chiarandini L, Brefeld U. Discriminative clustering for market segmentation. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. New York: Association for Computing Machinery, Inc. 2012. p. 417-425 doi: 10.1145/2339530.2339600

Bibtex

@inbook{5e0e09eff4a641fcb14544bc4ddc0bfd,
title = "Discriminative clustering for market segmentation",
abstract = "We study discriminative clustering for market segmentation tasks. The underlying problem setting resembles discriminative clustering, however, existing approaches focus on the prediction of univariate cluster labels. By contrast, market segments encode complex (future) behavior of the individuals which cannot be represented by a single variable. In this paper, we generalize discriminative clustering to structured and complex output variables that can be represented as graphical models. We devise two novel methods to jointly learn the classifier and the clustering using alternating optimization and collapsed inference, respectively. The two approaches jointly learn a discriminative segmentation of the input space and a generative output prediction model for each segment. We evaluate our methods on segmenting user navigation sequences from Yahoo! News. The proposed collapsed algorithm is observed to outperform baseline approaches such as mixture of experts. We showcase exemplary projections of the resulting segments to display the interpretability of the solutions. ",
keywords = "Informatics, Alternating optimizations, Discriminative clustering , GraphicaL model, Input space, Interpretability, Market segment, Market segmentation, Mixture of experts, Novel methods, Output variables, Prediction model, Single variable, Univariate, User navigation, Business informatics",
author = "Peter Haider and Luca Chiarandini and Ulf Brefeld",
year = "2012",
doi = "10.1145/2339530.2339600",
language = "English",
isbn = "978-1-4503-1462-6",
pages = "417--425",
booktitle = "Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining",
publisher = "Association for Computing Machinery, Inc",
address = "United States",
note = "18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD-2012 : Mining the Big Data, KDD 2012 ; Conference date: 12-08-2012 Through 16-08-2012",
url = "http://kdd2012.sigkdd.org/",

}

RIS

TY - CHAP

T1 - Discriminative clustering for market segmentation

AU - Haider, Peter

AU - Chiarandini, Luca

AU - Brefeld, Ulf

N1 - Conference code: 18

PY - 2012

Y1 - 2012

N2 - We study discriminative clustering for market segmentation tasks. The underlying problem setting resembles discriminative clustering, however, existing approaches focus on the prediction of univariate cluster labels. By contrast, market segments encode complex (future) behavior of the individuals which cannot be represented by a single variable. In this paper, we generalize discriminative clustering to structured and complex output variables that can be represented as graphical models. We devise two novel methods to jointly learn the classifier and the clustering using alternating optimization and collapsed inference, respectively. The two approaches jointly learn a discriminative segmentation of the input space and a generative output prediction model for each segment. We evaluate our methods on segmenting user navigation sequences from Yahoo! News. The proposed collapsed algorithm is observed to outperform baseline approaches such as mixture of experts. We showcase exemplary projections of the resulting segments to display the interpretability of the solutions.

AB - We study discriminative clustering for market segmentation tasks. The underlying problem setting resembles discriminative clustering, however, existing approaches focus on the prediction of univariate cluster labels. By contrast, market segments encode complex (future) behavior of the individuals which cannot be represented by a single variable. In this paper, we generalize discriminative clustering to structured and complex output variables that can be represented as graphical models. We devise two novel methods to jointly learn the classifier and the clustering using alternating optimization and collapsed inference, respectively. The two approaches jointly learn a discriminative segmentation of the input space and a generative output prediction model for each segment. We evaluate our methods on segmenting user navigation sequences from Yahoo! News. The proposed collapsed algorithm is observed to outperform baseline approaches such as mixture of experts. We showcase exemplary projections of the resulting segments to display the interpretability of the solutions.

KW - Informatics

KW - Alternating optimizations

KW - Discriminative clustering

KW - GraphicaL model

KW - Input space

KW - Interpretability

KW - Market segment

KW - Market segmentation

KW - Mixture of experts

KW - Novel methods

KW - Output variables

KW - Prediction model

KW - Single variable

KW - Univariate

KW - User navigation

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=84866039328&partnerID=8YFLogxK

U2 - 10.1145/2339530.2339600

DO - 10.1145/2339530.2339600

M3 - Article in conference proceedings

AN - SCOPUS:84866039328

SN - 978-1-4503-1462-6

SP - 417

EP - 425

BT - Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining

PB - Association for Computing Machinery, Inc

CY - New York

T2 - 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD-2012

Y2 - 12 August 2012 through 16 August 2012

ER -

DOI

Recently viewed

Publications

  1. Towards a Comprehensive Framework for Environmental Management Accounting
  2. Governmental activity, integration, and agglomeration
  3. Challenges in political interviews
  4. A switching model predictive control for overcoming a hysteresis effect in a hybrid actuator for camless internal combustion engines
  5. Towards a Comprehensive Framework for Environmental Management Accounting
  6. Actuator- and/or sensor element for sleeve in medical field e.g. limb or joint fracture treatment, has nano-wires comprising nano-fibers, where element deforms and acquires dimensional change of nano-fibers via electrical signal
  7. Article 32 Date of Application
  8. Collaborative modelling for active involvement of stakeholders in urban flood risk management
  9. Glitch(ing)! A refusal and gateway to more caring techno-urban worlds?
  10. Probing turbulent superstructures in Rayleigh-Bénard convection by Lagrangian trajectory clusters
  11. Assessing tree dendrometrics in young regenerating plantations using terrestrial laser scanning
  12. Toxicity testing with luminescent bacteria - Characterization of an automated method for the combined assessment of acute and chronic effects
  13. RelHunter
  14. Swarm Robotics, or: The Smartness of 'a bunch of cheap dumb things'
  15. Perceptions of Organizational Downsizing
  16. Policy implementation through multi-level governance
  17. Pre-service mathematics teachers' modelling processes within model eliciting activity through digital technologies
  18. Advantages and difficulties of conducting thinking-aloud protocols in the school setting
  19. Development of a procedure for forming assisted thermal joining of tubes
  20. The complementarity of single-species and ecosystem-oriented research in conservation research
  21. Innovation in Continuing Engineering Education with focus on gender and non-traditional students' pathways
  22. Does transition to IFRS substantially affect key financial ratios in shareholder-oriented common law regimes?
  23. Do it again
  24. Classification of playing position in elite junior Australian football using technical skill indicators
  25. Global patterns of ecologically unequal exchange
  26. The use of force against terrorists
  27. Wir sind ihr
  28. Delivering community benefits through REDD plus : Lessons from Joint Forest Management in Zambia
  29. Internet-Based Prevention of Depression in Employees
  30. Toward a Production-Oriented Imagology