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MATRIX is a world-class, award-winning learning management system (LMS) for businesses.
For small, medium, and large sized corporations, as well as associations and public organizations
The platform is known for delivering a great user experience, while incorporating all the essential tools companies need to support efficient training and learning.
Safe Harbor Deidentification for medical documents
Phalanx - Deidentify
Safe Harbor Deidentification Mode of Phalanx is an abridged pipeline of NLP annotators culminating in NER annotators which write output of text offsets. It uses the Safe Harbor deidentification method.
MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
This project is devoted to the development of natural language processing tools and resources for the Lingala language, which is spoken by tens of millions of people in central Africa.
This project aims to build a suite of Natural Language Processing tools. Modules will include corpus indexing and access tools, a part-of-speech tagger, tokenisers, text classification software, etc.
Axero Intranet is an award-winning intranet and employee experience platform.
Hundreds of companies and millions of employees use Axero’s intranet software to communicate, collaborate, manage tasks and events, organize content, and develop their company culture.
This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text.
The method is based on SVM but other ML algorithms can be adopted. The method details are explained in the...
D.U.C.K (Determine segmentation of Unknown words by using Context Knowledge)is an NLP tool, which aims to find the correct segmentation for unknown words in written Hebrew. Statistics from different scopes will be used to determine the segmentation.
MutationFinder is a biomedical natural language processing (NLP) system for extracting mentions of point mutations from free text. MutationFinder achieves high performance (99% precision, 81% recall on blind test data) as an information extraction system