This paper introduces a new kernel which computes similarity between two natural language sentences as the number of paths shared by their dependency trees. The paper gives a very efficient algorithm to compute it. This kernel is also an improvement over the word subsequence kernel because it only counts linguistically meaningful word subsequences which are based on word dependencies. It overcomes some of the difficulties encountered by syntactic tree kernels as well. Experimental results demonstrate the advantage of this kernel over word subsequence and syntactic tree kernels.

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In Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP-2008), pp. 400--409, Waikiki, Honolulu, Hawaii, October 2008.

@InProceedings{dependency-emnlp-08, title={A Dependency-based Word Subsequence Kernel}, author={Rohit J. Kate}, booktitle={Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP-2008)}, month={October}, address={Waikiki, Honolulu, Hawaii}, pages={400--409}, url="http://www.cs.utexas.edu/users/ai-lab?dependency-emnlp-08", year={2008} }