Text enrichment

Enrich your text data through state-of-the-art NLP and machine learning models: sentiment, topics, concepts, translation, and more.

9 articles in this collection
Written by Zafer Çavdar, Tomas Larsson, and Esra Binici

Sentiment analysis

The Analyze Sentiment operation analyzes the sentiment of input text through deep learning or sentiment lexicons.

Written by Tomas Larsson
Updated over a week ago

Emojization

The Emojize operation interprets the text and outputs the emojis that best capture the emotional nuances expressed.

Written by Zafer Çavdar
Updated over a week ago

Topic modeling

Use Detect Topics to identify topics in large volumes of unlabeled text.

Written by Zafer Çavdar
Updated over a week ago

Concept detection

The Detect Concepts operation finds the underlying concepts in the input text.

Written by Zafer Çavdar
Updated over a week ago

Language detection

The Detect Language operation detects the language of each input text and outputs the corresponding ISO 639-1 (2-letter) language code.

Written by Tomas Larsson
Updated over a week ago

Text-level machine translation

The Translate Text operation uses Google Translate to machine translate the input text.

Written by Tomas Larsson
Updated over a week ago

Word-level machine translation

Translate Words translates between any pair of 58 available languages, enabling multi-language analysis without full text-level translation.

Written by Zafer Çavdar
Updated over a week ago

Knowledge extraction

Enrich your data by extracting knowledge in the form of triplets

Written by Esra Binici
Updated over a week ago

Third-party NLP services

Provides access to third-party text enrichment services such as categorization and emotion recognition.

Written by Tomas Larsson
Updated over a week ago