@InProceedings{issaalaaaldine-EtAl:2018:S18-1,
  author    = {Issa Alaa Aldine, Ahmad  and  Harzallah, Mounira  and  Berio, Giuseppe  and  Béchet, Nicolas  and  Faour, Ahmad},
  title     = {EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {919--923},
  abstract  = {In this paper, we present our proposed system (EXPR) to participate in the hypernym discovery task of SemEval 2018. The task addresses the challenge of discovering hypernym relations from a text corpus. Our proposal is a combined approach of path-based technique and distributional technique. We use dependency parser on a corpus to extract candidate hypernyms and represent their dependency paths as a feature vector. The feature vector is concatenated with a feature vector obtained using Wikipedia pre-trained term embedding model. The concatenated feature vector fits a supervised machine learning method to learn a classifier model. This model is able to classify new candidate hypernyms as hypernym or not. Our system performs well to discover new hypernyms not defined in gold hypernyms.},
  url       = {http://www.aclweb.org/anthology/S18-1150}
}