Audience
Computational linguists and NLP researchers searching for a tool to improve their semantic analysis and language modeling
About LexVec
LexVec is a word embedding model that achieves state-of-the-art results in multiple natural language processing tasks by factorizing the Positive Pointwise Mutual Information (PPMI) matrix using stochastic gradient descent. This approach assigns heavier penalties for errors on frequent co-occurrences while accounting for negative co-occurrences. Pre-trained vectors are available, including a common crawl dataset with 58 billion tokens and 2 million words in 300 dimensions, and an English Wikipedia 2015 + NewsCrawl dataset with 7 billion tokens and 368,999 words in 300 dimensions. Evaluations demonstrate that LexVec matches or outperforms other models like word2vec in terms of word similarity and analogy tasks. The implementation is open source under the MIT License and is available on GitHub.
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Pricing
Starting Price:
Free
Free Version:
Free Version available.
Integrations
No integrations listed.
Company Information
Alexandre Salle
Brazil
github.com/alexandres/lexvec
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Product Details
Platforms Supported
Cloud
Windows
Mac
Linux
On-Premises
Training
Documentation
Support
Online
LexVec Frequently Asked Questions
Q: What kinds of users and organization types does LexVec work with?
LexVec works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does LexVec support in their product?
LexVec supports these languages: English.
Q: What kind of support options does LexVec offer?
LexVec offers support via online.
Q: What type of training does LexVec provide?
LexVec provides training in the form of documentation.
Q: How much does LexVec cost?
Pricing for LexVec starts at Free.
