dalinvip/cw2vec
cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information
This tool helps researchers and linguists analyze large volumes of Chinese text by generating numerical representations (embeddings) of words. You provide a text corpus in simplified Chinese, and it outputs word vectors that capture semantic relationships, which are useful for tasks like similarity analysis. It's designed for anyone working with Chinese language processing and understanding word meanings in context.
274 stars. No commits in the last 6 months.
Use this if you need to create high-quality word embeddings for Chinese text, particularly if you want to leverage stroke-level information to improve how words are represented.
Not ideal if you are working with languages other than Chinese or if you do not have computational linguistics experience, as it requires some technical setup.
Stars
274
Forks
66
Language
C++
License
Apache-2.0
Category
Last pushed
Mar 20, 2023
Commits (30d)
0
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