Iterative relational classification through three-state epidemic dynamics

Aram Galstyan, Paul R Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Relational classification in networked data plays an important role in many problems such as text categorization, classification of web pages, group finding in peer networks, etc. We have previously demonstrated that for a class of label propagating algorithms the underlying dynamics can be modeled as a two-state epidemic process on heterogeneous networks, where infected nodes correspond to classified data instances. We have also suggested a binary classification algorithm that utilizes non-trivial characteristics of epidemic dynamics. In this paper we extend our previous work by considering a three-state epidemic model for label propagation. Specifically, we introduce a new, intermediate state that corresponds to "susceptible" data instances. The utility of the added state is that it allows to control the rates of epidemic spreading, hence making the algorithm more flexible. We show empirically that this extension improves significantly the performance of the algorithm. In particular, we demonstrate that the new algorithm achieves good classification accuracy even for relatively large overlap across the classes.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages83-92
Number of pages10
Volume3975 LNCS
DOIs
StatePublished - 2006
Externally publishedYes
EventIEEE International Conference on Intelligence and Security Informatics, ISI 2006 - San Diego, CA, United States
Duration: May 23 2006May 24 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3975 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherIEEE International Conference on Intelligence and Security Informatics, ISI 2006
CountryUnited States
CitySan Diego, CA
Period5/23/065/24/06

Fingerprint

Labels
Epidemic Spreading
Text Categorization
Binary Classification
Heterogeneous Networks
Epidemic Model
Classification Algorithm
Heterogeneous networks
Overlap
Propagation
Websites
Vertex of a graph
Demonstrate
Class

Keywords

  • Binary classification
  • Relational learning

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Galstyan, A., & Cohen, P. R. (2006). Iterative relational classification through three-state epidemic dynamics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3975 LNCS, pp. 83-92). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3975 LNCS). https://doi.org/10.1007/11760146_8

Iterative relational classification through three-state epidemic dynamics. / Galstyan, Aram; Cohen, Paul R.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3975 LNCS 2006. p. 83-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3975 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Galstyan, A & Cohen, PR 2006, Iterative relational classification through three-state epidemic dynamics. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3975 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3975 LNCS, pp. 83-92, IEEE International Conference on Intelligence and Security Informatics, ISI 2006, San Diego, CA, United States, 5/23/06. https://doi.org/10.1007/11760146_8
Galstyan A, Cohen PR. Iterative relational classification through three-state epidemic dynamics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3975 LNCS. 2006. p. 83-92. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11760146_8
Galstyan, Aram ; Cohen, Paul R. / Iterative relational classification through three-state epidemic dynamics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3975 LNCS 2006. pp. 83-92 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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