Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
Retrieval performance in Ferret a conceptual information retrieval system
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Natural language information retrieval: progress report
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
Natural Language Information Retrieval
Natural Language Information Retrieval
Exploiting syntactic analysis of queries for information retrieval
Data & Knowledge Engineering
Kernels for Semi-Structured Data
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Comparing Hierarchical Data in External Memory
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
A survey on tree edit distance and related problems
Theoretical Computer Science
Tree kernels for semantic role labeling
Computational Linguistics
Using a Hybrid Convolution Tree Kernel for Semantic Role Labeling
ACM Transactions on Asian Language Information Processing (TALIP)
Algorithms for subsequence combinatorics
Theoretical Computer Science
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A methodology for clustering XML documents by structure
Information Systems
Efficient convolution kernels for dependency and constituent syntactic trees
ECML'06 Proceedings of the 17th European conference on Machine Learning
RTED: a robust algorithm for the tree edit distance
Proceedings of the VLDB Endowment
Pattern Recognition Letters
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Natural language processing based information retrieval (NIR) aims to go beyond the conventional bag-of-words based information retrieval (KIR) by considering syntactic and even semantic information in documents. NIR is a conceptually appealing approach to IR, but is hard due to the need to measure distance/similarity between structures. We aim to move beyond the state of the art in measuring structure similarity for NIR. In this paper, a novel tree similarity measurement dtwAcs is proposed in terms of a novel interpretation of trees as multi dimensional sequences. We calculate the distance between trees by the way of computing the distance between multi dimensional sequences, which is conducted by integrating the all common subsequences into the dynamic time warping method. Experimental result shows that dtwAcs outperforms the state of the art.