Integrating Lexical Knowledge in Word Embeddings using Sprinkling and Retrofitting
Table 5: Word Similarity results for W-Retrofitting approach
['Method', 'Lexical Knowledge', 'Similarity Hops', 'Similarity SimLex999', 'Similarity WS353S', 'Similarity RG65', 'Relatedness WS353R', 'Relatedness TR9856', 'Relatedness MTurk', 'No Distinction WS353', 'No Distinction MEN', 'No Distinction RW']
We see that using PPDB knowledge source and path based similarity as weights in the retrofit objective functions gives the best performance and outperforms the baselines in most benchmarks.