@inproceedings{ranjbar-etal-2017-mahtab,
title = "Mahtab at {S}em{E}val-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity",
author = "Ranjbar, Niloofar and
Mashhadirajab, Fatemeh and
Shamsfard, Mehrnoush and
Hosseini pour, Rayeheh and
Vahid pour, Aryan",
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/S17-2040",
doi = "10.18653/v1/S17-2040",
pages = "256--260",
abstract = "In this paper, we describe our proposed method for measuring semantic similarity for a given pair of words at SemEval-2017 monolingual semantic word similarity task. We use a combination of knowledge-based and corpus-based techniques. We use FarsNet, the Persian Word Net, besides deep learning techniques to extract the similarity of words. We evaluated our proposed approach on Persian (Farsi) test data at SemEval-2017. It outperformed the other participants and ranked the first in the challenge.",
}
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%0 Conference Proceedings
%T Mahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity
%A Ranjbar, Niloofar
%A Mashhadirajab, Fatemeh
%A Shamsfard, Mehrnoush
%A Hosseini pour, Rayeheh
%A Vahid pour, Aryan
%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 ranjbar-etal-2017-mahtab
%X In this paper, we describe our proposed method for measuring semantic similarity for a given pair of words at SemEval-2017 monolingual semantic word similarity task. We use a combination of knowledge-based and corpus-based techniques. We use FarsNet, the Persian Word Net, besides deep learning techniques to extract the similarity of words. We evaluated our proposed approach on Persian (Farsi) test data at SemEval-2017. It outperformed the other participants and ranked the first in the challenge.
%R 10.18653/v1/S17-2040
%U https://aclanthology.org/S17-2040
%U https://doi.org/10.18653/v1/S17-2040
%P 256-260
Markdown (Informal)
[Mahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity](https://aclanthology.org/S17-2040) (Ranjbar et al., SemEval 2017)
ACL