Graph based multi-view learning for CDL relation classification

Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka

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

2 Citations (Scopus)

Abstract

To understand text contents better, many research efforts have been made exploring detection and classification of the semantic relation between a concept pair. As described herein, we present our study of a semantic relation classification task as a graph-based multi-view learning task: each intra-view graph is constructed with instances in the view; a node's label "score" is propagated on each intra-view graph and inter-view graph. This combination of multi-view learning and graph-based method can reduce the influence from violation of a background assumption of multi-view learning algorithms - view compatibility. The proposed algorithm is evaluated using the Concept Description Language for Natural Language (CDL.nl) corpus. The experiment results validate its effectiveness.

Original languageEnglish
Title of host publicationICSC 2009 - 2009 IEEE International Conference on Semantic Computing
Pages473-480
Number of pages8
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventICSC 2009 - 2009 IEEE International Conference on Semantic Computing - Berkeley, CA
Duration: 2009 Sep 142009 Sep 16

Other

OtherICSC 2009 - 2009 IEEE International Conference on Semantic Computing
CityBerkeley, CA
Period09/9/1409/9/16

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Semantics
Learning algorithms
Labels
Experiments

Keywords

  • CDL
  • Graph based model
  • Multi-view learning
  • Relation classification
  • Semi-supervised learning

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Electrical and Electronic Engineering

Cite this

Li, H., Matsuo, Y., & Ishizuka, M. (2009). Graph based multi-view learning for CDL relation classification. In ICSC 2009 - 2009 IEEE International Conference on Semantic Computing (pp. 473-480). [5298632] https://doi.org/10.1109/ICSC.2009.97

Graph based multi-view learning for CDL relation classification. / Li, Haibo; Matsuo, Yutaka; Ishizuka, Mitsuru.

ICSC 2009 - 2009 IEEE International Conference on Semantic Computing. 2009. p. 473-480 5298632.

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

Li, H, Matsuo, Y & Ishizuka, M 2009, Graph based multi-view learning for CDL relation classification. in ICSC 2009 - 2009 IEEE International Conference on Semantic Computing., 5298632, pp. 473-480, ICSC 2009 - 2009 IEEE International Conference on Semantic Computing, Berkeley, CA, 09/9/14. https://doi.org/10.1109/ICSC.2009.97
Li H, Matsuo Y, Ishizuka M. Graph based multi-view learning for CDL relation classification. In ICSC 2009 - 2009 IEEE International Conference on Semantic Computing. 2009. p. 473-480. 5298632 https://doi.org/10.1109/ICSC.2009.97
Li, Haibo ; Matsuo, Yutaka ; Ishizuka, Mitsuru. / Graph based multi-view learning for CDL relation classification. ICSC 2009 - 2009 IEEE International Conference on Semantic Computing. 2009. pp. 473-480
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