Text Analytics Toolbox™ provides algorithms and visualizations for preprocessing, analyzing, and modeling text data. Models created with the toolbox can be used in applications such as sentiment analysis, predictive maintenance, and topic modeling.
Text Analytics Toolbox includes tools for processing raw text from sources such as equipment logs, news feeds, surveys, operator reports, and social media. You can extract text from popular file formats, preprocess raw text, extract individual words, convert text into numerical representations, and build statistical models.
Using machine learning techniques such as LSA, LDA, and word embeddings, you can find clusters and create features from high-dimensional text datasets. Features created with Text Analytics Toolbox can be combined with features from other data sources to build machine learning models that take advantage of textual, numeric, and other types of data.
Discover more about Text Analytics Toolbox by exploring these resources.
Explore documentation for Text Analytics Toolbox functions and features, including release notes and examples.
Browse the list of available Text Analytics Toolbox functions.
View system requirements for the latest release of Text Analytics Toolbox.
Use Text Analytics Toolbox to solve scientific and engineering challenges: