@inproceedings{rotari-etal-2017-wild,
title = "Wild Devs{'} at {S}em{E}val-2017 Task 2: Using Neural Networks to Discover Word Similarity",
author = "Rotari, R{\u{a}}zvan-Gabriel and
Hulub, Ionu{\textcommabelow{t}} and
Oprea, {\textcommabelow{S}}tefan and
Pl{\u{a}}mad{\u{a}}-Onofrei, Mihaela and
Loren{\c{t}}, Alina Beatrice and
Preisler, Raluca and
Iftene, Adrian and
Trandab{\u{a}}{\textcommabelow{t}}, Diana",
editor = "Bethard, Steven and
Carpuat, Marine and
Apidianaki, Marianna and
Mohammad, Saif M. and
Cer, Daniel and
Jurgens, David",
booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S17-2042",
doi = "10.18653/v1/S17-2042",
pages = "267--270",
abstract = "This paper presents Wild Devs{'} participation in the SemEval-2017 Task 2 {``}Multi-lingual and Cross-lingual Semantic Word Similarity{''}, which tries to automatically measure the semantic similarity between two words. The system was build using neural networks, having as input a collection of word pairs, whereas the output consists of a list of scores, from 0 to 4, corresponding to the degree of similarity between the word pairs.",
}
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<abstract>This paper presents Wild Devs’ participation in the SemEval-2017 Task 2 “Multi-lingual and Cross-lingual Semantic Word Similarity”, which tries to automatically measure the semantic similarity between two words. The system was build using neural networks, having as input a collection of word pairs, whereas the output consists of a list of scores, from 0 to 4, corresponding to the degree of similarity between the word pairs.</abstract>
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%0 Conference Proceedings
%T Wild Devs’ at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity
%A Rotari, Răzvan-Gabriel
%A Hulub, Ionu\textcommabelowt
%A Oprea, \textcommabelowStefan
%A Plămadă-Onofrei, Mihaela
%A Lorenţ, Alina Beatrice
%A Preisler, Raluca
%A Iftene, Adrian
%A Trandabă\textcommabelowt, Diana
%Y Bethard, Steven
%Y Carpuat, Marine
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y Cer, Daniel
%Y Jurgens, David
%S Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F rotari-etal-2017-wild
%X This paper presents Wild Devs’ participation in the SemEval-2017 Task 2 “Multi-lingual and Cross-lingual Semantic Word Similarity”, which tries to automatically measure the semantic similarity between two words. The system was build using neural networks, having as input a collection of word pairs, whereas the output consists of a list of scores, from 0 to 4, corresponding to the degree of similarity between the word pairs.
%R 10.18653/v1/S17-2042
%U https://aclanthology.org/S17-2042
%U https://doi.org/10.18653/v1/S17-2042
%P 267-270
Markdown (Informal)
[Wild Devs’ at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity](https://aclanthology.org/S17-2042) (Rotari et al., SemEval 2017)
ACL
- Răzvan-Gabriel Rotari, Ionuț Hulub, Ștefan Oprea, Mihaela Plămadă-Onofrei, Alina Beatrice Lorenţ, Raluca Preisler, Adrian Iftene, and Diana Trandabăț. 2017. Wild Devs’ at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 267–270, Vancouver, Canada. Association for Computational Linguistics.