2006 TreeStructuredConditionalRandom

(Tang et al., 2006) ⇒ Jie Tang, Mingcai Hong, Juanzi Li, and Bangyong Liang. (2006). “Tree-structured Conditional Random Fields for Semantic Annotation.” In: Proceedings of the 5th International Conference on The Semantic Web. doi:10.1007/11926078_46

Subject Headings: Tree-Structured CRF Model.

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Abstract

The large volume of web content needs to be annotated by ontologies (called Semantic Annotation), and our empirical study shows that strong dependencies exist across different types of information (it means that identification of one kind of information can be used for identifying the other kind of information). Conditional Random Fields (CRFs) are the state-of-the-art approaches for modeling the dependencies to do better annotation. However, as information on a Web page is not necessarily linearly laid-out, the previous linear-chain CRFs have their limitations in semantic annotation. This paper is concerned with semantic annotation on hierarchically dependent data (hierarchical semantic annotation). We propose a Tree-structured Conditional Random Field (TCRF) model to better incorporate dependencies across the hierarchically laid-out information. Methods for performing the tasks of model-parameter estimation and annotation in TCRFs have been proposed. Experimental results indicate that the proposed TCRFs for hierarchical semantic annotation can significantly outperform the existing linear-chain CRF model.

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References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2006 TreeStructuredConditionalRandom	Jie Tang Juanzi Li Mingcai Hong Bangyong Liang			Tree-structured Conditional Random Fields for Semantic Annotation				10.1007/11926078_46