The acquisition of synonyms and quasi-synonyms of multi-word terms (MWTs) is a relatively new and under represented topic of research. However, dealing with MWT synonyms and semantically related terms is a challenging task, especially when MWT synonyms are single word terms (SWTs) or MWTs of different lengths. While several researches addressed synonym extraction of SWTs, few of them dealt with MWTs and fewer or none while MWTs synonyms are of variable lengths. The present research aims at introducing a new word-embedding-based approach for the automatic acquisition of synonyms of MWTs that manage length variability. We evaluate our approach on two specialized domain corpora, a French/English corpus of the wind energy domain and a French/English corpus of the breast cancer domain and show superior results compared to baseline approaches.
@InProceedings{HAZEM18.36, author = {Amir Hazem and Béatrice Daille}, title = "{Word Embedding Approach for Synonym Extraction of Multi-Word Terms}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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