Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings
Table 8: Comparison between SG and SG + Exp regarding word pair 
['[BOLD] Model', '[BOLD] Sim', '[BOLD] Closest to “censorships”']
We see that the words “censorship” and its rarer morphological variant “censorships” have very low similarity score and the similar words for “censorships” are also not very informative. By training new embeddings on the expanded corpus we find that not only does the similarity score increase but the other moprhological variants also come closer to the word.