2017 RUFINOatSemEval2017Task2CrossLi

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Subject Headings: RUFINO; Multilingual And Cross-Lingual Semantic Word Similarity System; SemEval-2017 Task 2.

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Cited By

Quotes

Abstract

The RUFINO team proposed a non-supervised, conceptually-simple and low-cost approach for addressing the Multilingual and Cross-lingual Semantic Word Similarity challenge at SemEval 2017. The proposed systems were cross-lingual extensions of popular monolingual lexical similarity approaches such as PMI and word2vec. The extensions were possible by means of a small parallel list of concepts similar to the Swadesh'™s list, which we obtained in a semi-automatic way. In spite of its simplicity, our approach showed to be effective obtaining statistically-significant and consistent results in all datasets proposed for the task. Besides, we provide some research directions for improving this novel and affordable approach.

References

BibTeX

@inproceedings{2017_RUFINOatSemEval2017Task2CrossLi,
  author    = {Sergio Jimenez and
               George Duenas and
               Lorena Gaitan and
               Jorge Segura},
  editor    = {Steven Bethard and
               Marine Carpuat and
               Marianna Apidianaki and
               Saif M. Mohammad and
               Daniel M. Cer and
               David Jurgens},
  title     = {RUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity
               by extending PMI and word embeddings systems with a Swadesh's-like
               list},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation
               (SemEval@ACL 2017)},
  pages     = {239--244},
  publisher = {Association for Computational Linguistics},
  year      = {2017},
  url       = {https://doi.org/10.18653/v1/S17-2037},
  doi       = {10.18653/v1/S17-2037},
}


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2017 RUFINOatSemEval2017Task2CrossLiSergio Jimenez
George Duenas
Lorena Gaitan
Jorge Segura
RUFINO at SemEval-2017 Task 2: Cross-lingual Lexical Similarity by Extending PMI and Word Embeddings Systems with a Swadesh's-like List2017