A Syntactico-Semantic Method for Arabic Collocations Extraction
Chiraz Ben Othmane Zribi, Bechir Baghouli · 2017
This work focuses on the extraction of collocations from Arabic textual corpora. The method that we propose is hybrid. It uses syntactico-semantic information by combining an enriched linguistic filtering with a statistical filtering. Linguistic filtering applies syntactic patterns represented by finite state automata and considers both elementary collocations and augmented ones. Statistical filtering is novel since it does not use classical association measures and applies the Latent Semantic Analysis (LSA) method to infer deeper semantic relations than those derived by contiguity frequencies, co-occurrence counts, or correlations in usage. The experiments showed that LSA gives globally better results than those achieved by Mutual Information (MI), Likelihood ration (LLR), Khi-Carré (X2), z score and t-test.