Mahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity

@inproceedings{Ranjbar2017MahtabAS,
  title={Mahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity},
  author={Niloofar Ranjbar and Fatemeh Mashhadirajab and Mehrnoush Shamsfard and Rayeheh Hosseini pour and Aryan Vahid pour},
  booktitle={SemEval@ACL},
  year={2017}
}
In this paper, we describe our proposed method for measuring semantic similarity for a given pair of words at SemEval2017 monolingual semantic word similarity task. We use a combination of knowledge-based and corpus-based techniques. We use FarsNet, the Persian WordNet, 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.