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Mathematica – provides built in tools for text alignment, pattern matching, clustering and semantic analysis. See Wolfram Language , the programming language of Mathematica. MATLAB offers Text Analytics Toolbox for importing text data, converting it to numeric form for use in machine and deep learning, sentiment analysis and classification tasks.
Voyant Tools is an open-source, web-based application for performing text analysis. It supports scholarly reading and interpretation of texts or corpus, particularly by scholars in the digital humanities , but also by students and the general public.
In the United States, the School of Information at University of California, Berkeley is developing a program called BioText to assist biology researchers in text mining and analysis. The Text Analysis Portal for Research (TAPoR), currently housed at the University of Alberta, is a scholarly project to catalogue text analysis applications and ...
TAPoR (Text Analysis Portal for Research) is a gateway that highlights tools and code snippets usable for textual criticism of all types. The project is housed at the University of Alberta, and is currently led by Geoffrey Rockwell, Stéfan Sinclair, Kirsten C. Uszkalo, and Milena Radzikowska.
Piranha is a text mining system. It was developed for the United States Department of Energy (DOE) by Oak Ridge National Laboratory (ORNL). The software processes free-text documents and shows relationships amongst them, a technique valuable across numerous data domains, from health care fraud to national security.
KH Coder is an open source software for computer assisted qualitative data analysis, particularly quantitative content analysis and text mining. It can be also used for computational linguistics. It supports processing and etymological information of text in several languages, such as Japanese, English, French, German, Italian, Portuguese and ...
Apache cTAKES: clinical Text Analysis and Knowledge Extraction System is an open-source Natural Language Processing (NLP) system that extracts clinical information from electronic health record unstructured text. It processes clinical notes, identifying types of clinical named entities — drugs, diseases/disorders, signs/symptoms, anatomical ...
Relate unstructured text with structured data such as dates, numbers or categorical data for identifying temporal trends or differences between subgroups or for assessing relationship with ratings or other kind of categorical or numerical data. Visualization tools to visualize and interpret text analysis results: Dendrogram with optional bar chart
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