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Graph Based Multi-View Learning for CDL Relation Classification

TitleGraph Based Multi-View Learning for CDL Relation Classification
Publication TypeConference Paper
Year of Publication2009
AuthorsLi, H, Matsuo, Y, Ishizuka, M
Conference NameInternational Conference on Semantic Computing
PublisherIEEE Computer Society
Conference LocationLos Alamitos, CA, USA
ISBN Number978-0-7695-3800-6
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.

DOI10.1109/ICSC.2009.97