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A Study on Similarity and Relatedness Using Distributional and WordNet-based Approaches

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If you have a question about this talk, please contact Diarmuid Ó Séaghdha.

At this session of the NLIP Reading Group we’ll be discussing the following paper:

Eneko Agirre, Enrique Alfonseca, Keith Hall, Jana Kravalova, Marius Pasca and Aitor Soroa. 2009. A Study on Similarity and Relatedness Using Distributional and WordNet-based Approaches. In Proceedings of NAACL -HLT 2009.

Abstract: This paper presents and compares WordNet-based and distributional similarity approaches. The strengths and weaknesses of each approach regarding similarity and relatedness tasks are discussed, and a combination is presented. Each of our methods independently provide the best results in their class on the RG and WordSim353 datasets, and a supervised combination of them yields the best published results on all datasets. Finally, we pioneer cross-lingual similarity, showing that our methods are easily adapted for a cross-lingual task with minor losses.

This talk is part of the Natural Language Processing Reading Group series.

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