How do you evaluate Word2Vec embedding quality on a domain corpus?medium
Answer
Word analogy tasks (king - man + woman = queen), word similarity benchmarks, and domain-specific nearest-neighbor inspection (is 'neural network' close to 'deep learning'?).
Explanation
Word analogy tasks (king - man + woman = queen), word similarity benchmarks, and domain-specific nearest-neighbor inspection (is 'neural network' close to 'deep learning'?). Downstream eval: did cosine similarity ranking correlate with human recruiter judgments? Also visualized with t-SNE to verify clustering of related CS concepts.
Follow-upWhat tradeoffs did you consider in that implementation?