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Description
The Exa API provides access to premier online content through an embeddings-focused search methodology.
By comprehending the underlying meaning of queries, Exa delivers results that surpass traditional search engines.
Employing an innovative link prediction transformer, Exa effectively forecasts connections that correspond with a user's specified intent.
For search requests necessitating deeper semantic comprehension, utilize our state-of-the-art web embeddings model tailored to our proprietary index, while for more straightforward inquiries, we offer a traditional keyword-based search alternative.
Eliminate the need to master web scraping or HTML parsing; instead, obtain the complete, clean text of any indexed page or receive intelligently curated highlights ranked by relevance to your query.
Users can personalize their search experience by selecting date ranges, specifying domain preferences, choosing a particular data vertical, or retrieving up to 10 million results, ensuring they find exactly what they need.
This flexibility allows for a more tailored approach to information retrieval, making it a powerful tool for diverse research needs.
Description
Word2Vec is a technique developed by Google researchers that employs a neural network to create word embeddings. This method converts words into continuous vector forms within a multi-dimensional space, effectively capturing semantic relationships derived from context. It primarily operates through two architectures: Skip-gram, which forecasts surrounding words based on a given target word, and Continuous Bag-of-Words (CBOW), which predicts a target word from its context. By utilizing extensive text corpora for training, Word2Vec produces embeddings that position similar words in proximity, facilitating various tasks such as determining semantic similarity, solving analogies, and clustering text. This model significantly contributed to the field of natural language processing by introducing innovative training strategies like hierarchical softmax and negative sampling. Although more advanced embedding models, including BERT and Transformer-based approaches, have since outperformed Word2Vec in terms of complexity and efficacy, it continues to serve as a crucial foundational technique in natural language processing and machine learning research. Its influence on the development of subsequent models cannot be overstated, as it laid the groundwork for understanding word relationships in deeper ways.
API Access
Has API
API Access
Has API
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Integrations
Anything
BrainyAI
Composio
Disco.dev
Gensim
Nango
OpenTools
ToolSDK.ai
Integrations
Anything
BrainyAI
Composio
Disco.dev
Gensim
Nango
OpenTools
ToolSDK.ai
Pricing Details
$100 per month
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Exa.ai
Country
United States
Website
exa.ai/
Vendor Details
Company Name
Founded
1998
Country
United States
Website
code.google.com/archive/p/word2vec/