Rosette is now part of Babel Street! Read more >>

Tag: Topic Extraction

Topic extraction is an NLP capability that automatically extracts keyphrases and concepts from a given text based on frequency and linguistic patterns. Keyphrases, i.e. keywords, are significant phrases that are present in the text. Concepts are themes that may or may no not be explicitly mentioned in the text.

You can find our recent articles about topic extraction on this page.

The Thanksgiving Turkey Pardon as Seen by Rosette

Thanksgiving has grown into a melting pot of different traditions with more than just delicious food to offer. One tradition that sparked our interest was the pardoning of the Thanksgiving turkey, as it’s been celebrated for decades!   Since the Presidency of John F. Kennedy, it’s become a tradition for the president in office to issue […]

Rosette Cloud 1.9: More Languages, Higher Accuracy, and Deep Neural Nets

Rosette Cloud 1.9 is out, delivering a new language for name matching, translation, and deduplication: Thai. We’ve also added a new deep neural network model for sentiment analysis, entity extraction offsets, salience scores for topic extraction, and more. Learn more below, or jump to the release notes. Name Matching The /name-similarity, /name-translation, and /name-deduplication endpoints […]

A Document’s Vital Stats: Keyphrases and Concepts

New Rosette Cloud topics endpoint enables summarization, content organization and trend analysis We are creating new content online at an unprecedented rate. Globally, we compose 3.6 trillion words every day on email and social media, the equivalent of 36 million books.* Managing and deriving value from that volume of text data can only hope to […]