This multilingual eDiscovery effort used text analytics and machine translation to effectively prioritize unreviewed materials. The result: 151% more productivity, saving time and money.
We’ve recently released this whitepaper which explores a new way to solve cross-lingual semantic search. Rather than use machine translation to translate queries or search records, this approach delivers better accuracy based on semantics, not translation. Semantic search (aka, concept search) goes beyond finding keywords, to retrieving ideas suggested by the keywords. In part 1 […]
We’re thrilled to announce the latest version of Rosette (1.11). It’s a big one — lots of exciting new features, enhancements, and improvements. We hope you’ll check it out! TL; DR check the release notes. Entities: Enhanced Extraction and Linking with New Types Rosette Entity Extraction & Linking now recognizes 700 new classes of entities […]
Rosette’s name matching is enhanced by word embeddings to match based on semantics as well as phonetics Tracking mentions of particular organizations across news articles, social media, and internal communications is integral to the workflow of dozens of use-cases across industries. However it can be especially challenging to match names of companies and organizations because […]
A Crash Course in Basic Text Embeddings A chronic problem with using machines to analyze human language is that the same meaning can be expressed using many different words. Take for example the sentence “Bill Gates was educated at Harvard.” There are many ways to express this relationship: Bill Gates studied at Harvard, Bill Gates […]
Text Embeddings Now Available in the Rosette API The Rosette API team is excited to announce the addition of a new function to Rosette’s suite of capabilities: text embedding. This endpoint returns a single vector of floating point numbers for your input, a.k.a. an embedding of your text in a semantic vector space. Text embeddings […]