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https://github.com/yoch/jmp8
SemEval-2017 Task 2 (subtask 1), supplemental material
https://github.com/yoch/jmp8
nlp semantic-similarity semeval
Last synced: 10 days ago
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SemEval-2017 Task 2 (subtask 1), supplemental material
- Host: GitHub
- URL: https://github.com/yoch/jmp8
- Owner: yoch
- Created: 2017-02-23T18:58:48.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2017-11-19T14:07:30.000Z (about 7 years ago)
- Last Synced: 2024-11-05T23:11:53.315Z (about 2 months ago)
- Topics: nlp, semantic-similarity, semeval
- Language: Python
- Homepage:
- Size: 783 KB
- Stars: 0
- Watchers: 4
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# SemEval-2017 Task 2 (subtask 1), supplemental material
To cite this work, please use :
```
@InProceedings{melka-bernard:2017:SemEval,
author = {Melka, Josu\'{e} and Bernard, Gilles},
title = {Jmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarity},
booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
month = {August},
year = {2017},
address = {Vancouver, Canada},
publisher = {Association for Computational Linguistics},
pages = {230--234},
abstract = {We have built a simple corpus-based system to estimate words similarity in
multiple languages with a count-based approach. After training on Wikipedia
corpora, our system was evaluated on the multilingual subtask of SemEval-2017
Task 2 and achieved a good level of performance, despite its great simplicity.
Our results tend to demonstrate the power of the distributional approach in
semantic similarity tasks, even without knowledge of the underlying language.
We also show that dimensionality reduction has a considerable impact on the
results.},
url = {http://www.aclweb.org/anthology/S17-2035}
}
```