Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model
Table 3: Word similarity evaluation on WordSim353 . IESG indicates our proposed image-enhanced skip-gram model. We use Spearman rank to evaluate the correlation. P-values are all below 1e-5.
['Model', 'Similarity', 'Relatedness']
This indicates that our model can embody the image information into word embeddings without hurting the semantic knowledge learned from text.