• April 12, 2016

Basis Technology Delivers Cloud-Based Text Analytics

Basis Technology, a provider of multilingual text analytics, today released Rosette API, applying artificial intelligence to understanding human language, sentiment analysis, relationship extraction, and document categorization.

"There are many cloud offerings on the market, but none that perform text analysis in a wide range of languages at consistently high levels of quality," said Basis Technology CEO Carl Hoffman in a statement. "Rosette API meets the demand from innovators who are transforming markets, businesses, and industries."

Subscribers to Rosette API receive a rthe following analytic capabilities:

  • Morphological Analysis, including lemmatization, decompounding, and part-of-speech identification;
  • Entity Extraction and Entity Linking, identifying people, places, and organizations and connecting them to real-world usage;
  • Name Matching and Name Translation, extending across multiple cultures, scripts, and languages;
  • Relationship Extraction, discovering how people, places, and organizations relate across multiple documents;
  • Sentiment Analysis, revealing feelings about products;
  • Categorization, automatically organizing documents into a taxonomy; and
  • Language Identification, identifying language boundaries within documents.

Developers can access Rosette API via Python, Node.js, PHP, and other programming languages. RapidMiner users can consume Rosette API in their predictive analytics workflows.

New features that find adoption among API users will also be available in an on-premises offering.

"Natural language processing enables essential features across countless applications. Rosette API makes this technology accessible to developers working in the most popular development platforms, speeding products to market," said Gregor Stewart, vice president of product management at Basis Technology, in a statement. "Going forward, Rosette API subscribers will be able to customize their text analysis environment and use specialty text analytics models tailored to specific industry use cases."


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