Text Classification
By MeaningCloud
Updated 9 months ago
Text Classification Overview
Automatic multilingual text classification according to pre-established categories defined in a model. The algorithm used combines statistic classification with rule-based filtering, which allows to obtain a high degree of precision for very different environments. Three models available: IPTC (International Press Telecommunications Council standard), EuroVocs and Corporate Reputation model. Languages covered are Spanish, English, French, Italian, Portuguese and Catalan.
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MeaningCloud's Text Classification

Assigns one or more categories to a text, using standard domain-specific taxonomies (e.g., IPTC. IAB, ICD-10) or user-defined categories. The algorithm combines statistical document classification with rule-based filtering, which allows to obtain a high degree of accuracy and flexibility in a wide range of environments.


  • Statistical classifiers provide a means to use example documents to define each category.
  • In turn, rule base classifiers helps to fine-tune the classification and correct the output of statistical classifiers.
  • Its powerful rule based classification language is also useful to bootstrap a categorization when no examples are available.
  • Features predefined, standard taxonomies: IPTC, IAB, ICD-10, Eurovoc.
  • User can create its own categories and classification models.
  • FREE for up to 20,000 requests per month.

More information at http://www.meaningcloud.com/products/text-classification/

Related APIs:
Topics Extraction https://rapidapi.com/MeaningCloud/api/topics-extraction
Sentiment Analysis https://rapidapi.com/MeaningCloud/api/sentiment-analysis
Language Identification https://rapidapi.com/MeaningCloud/api/language-identification

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