Abstract
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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Ribadas, F.J., Vilares, M., Vilares, J. (2005). Semantic Similarity Between Sentences Through Approximate Tree Matching. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_78
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DOI: https://doi.org/10.1007/11492542_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
Online ISBN: 978-3-540-32238-2
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