We describe an algorithm to measure the similarity between sentences, integrating the edit distance between trees and single-term similarity techniques, and also allowing the pattern to be defined approximately, omitting some structural details. A technique of this kind is of interest in a variety of applications, such as information extraction/retrieval or question answering, where error-tolerant recognition allows incomplete sentences to be integrated in the computation process. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Ribadas, F. J., Vilares, M., & Vilares, J. (2005). Semantic similarity between sentences through approximate tree matching. In Lecture Notes in Computer Science (Vol. 3523, pp. 638–646). Springer Verlag. https://doi.org/10.1007/11492542_78
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