Class Meeting for 10-707 10/14/2009

This is one of the class meetings on the schedule for the course Information Extraction 10-707 in Fall 2009.

Relation learning with kernels

• Slides

Required Readings

• Subsequence kernels for relation extraction, by R. Bunescu, R. Mooney. In Advances in Neural Information Processing Systems, 2006.
• A shortest path dependency kernel for relation extraction, by Razvan C Bunescu, Raymond J Mooney. In HLT '05: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, 2005.

Optional Readings

• Kernel Conditional Random Fields: ..., Lafferty et al, ICML 2004. An approach to kernelizing CRFs - not an easy read but worthwhile.
• Exploring Syntactic Features for Relation Extraction using a Convolution Tree Kernel, Zhang et al, HLT 2006. Tree kernels for dependency parses.
• Joint Extraction of Entities and Relations for Opinion Recognition, Choi, Breck, Cardie, EMNLP 2006. Uses the Yih & Roth technique of incorporating constraints at classification time via an ILP problem.
• A Rich Feature Vector for Protein-Protein Interaction Extraction from Multiple Corpora, by M. Miwa, R. S\aetre, Y. Miyao, J. Tsujii. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009.. Using some fancy kernel tricks to learn a particular type of relation (protein-protein interaction).
• Classifying Relations for Biomedical Named Entity Disambiguation, by Xinglong Wang, {{{coauthors}}}. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009.. An interesting twist on classifying relations, via classification of keywords as informative or not.