How to Generate a Good Word Embedding?
Table 7: PGR values for the CBOW model trained on different corpora.
['[BOLD] Corpus', '[BOLD] syn', '[BOLD] sem', '[BOLD] ws', '[BOLD] tfl', '[BOLD] avg', '[BOLD] ner', '[BOLD] cnn', '[BOLD] pos']
We choose a representative model CBOW to analyze the influence of the corpus because of the space limitation. The other models yield similar results. The best PGR for each task is 100%. , we can conclude that using a larger corpus can yield a better embedding, when the corpora are in the same domain. We compare the full-sized NYT corpus with its 100M subset, the Wiki corpus with its subset, and the W&N corpus with its three subsets. In almost all cases, the larger corpus is superior to the smaller corpus. The observed exceptions may be attributable to instability of the evaluation metrics.