2013 AlignDisambiguateandWalkAUnifie

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Subject Headings: Align-Disambiguate-Walk (ADW) Semantic Similarity System; Semantic Word Similarity; Semantic Textual Similarity; Alignment-based Sense Disambiguation Algorithm; Random Walk-based Sense Disambiguation Algorithm.

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Quotes

Abstract

Semantic similarity is an essential component of many Natural Language Processing applications. However, prior methods for computing semantic similarity often operate at different levels, e.g., single words or entire documents, which requires adapting the method for each data type. We present a unified approach to semantic similarity that operates at multiple levels, all the way from comparing word senses to comparing text documents. Our method leverages a common probabilistic representation over word senses in order to compare different types of linguistic data. This unified representation shows state-of-the-art performance on three tasks: semantic textual similarity, word similarity, and word sense coarsening.

References

BibTeX

@inproceedings{2013_AlignDisambiguateandWalkAUnifie,
  author    = {Mohammad Taher Pilehvar and
               David Jurgens and
               Roberto Navigli},
  title     = {Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic
               Similarity},
  booktitle = {Proceedings of the 51st Annual Meeting of the Association for Computational
               Linguistics (ACL 2013) Volume 1: Long Papers},
  pages     = {1341--1351},
  publisher = {The Association for Computer Linguistics},
  year      = {2013},
  url       = {https://aclanthology.org/P13-1132/},
}


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2013 AlignDisambiguateandWalkAUnifieDavid Jurgens
Mohammad Taher Pilehvar
Roberto Navigli
Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity2013