Chinese Embedding via Stroke and Glyph Information:A Dual-channel View
Table 1: Performance on word similarity and word analogy task. The dimension of embeddings is set as 300. The evaluation metric is ρ for word similarity and accuracy percentage for word analogy.
['Model', 'Word Similarity', 'Word Similarity', 'Word Analogy 3CosAdd', 'Word Analogy 3CosAdd', 'Word Analogy 3CosAdd', 'Word Analogy 3CosMul', 'Word Analogy 3CosMul', 'Word Analogy 3CosMul']
We can observe that our DWE model achieves the best results both on dataset wordsim-240 and wordsim-296 in the similarity task as expected because of the particularity of Chinese morphology, but it only improves the accuracy for the family group in the analogy task.