Open Source Java Linguistics Software

CLEiM (Cross Lingual Education in Medicine) is an opensource version of an Intelligent System which extract concepts from medical texts and provides qualified information. It integrates information from various sources. This system has been developed by the Intelligent System Group GSI (http://www.esi.uem.es/gsi/) at UEM University. We do NER (Named Entity Recognition) based on GATE platform. The installation is simple, you can use it as a Web application. It has been tested under apache-tomcat. The original system has been successfully used to carry out active learning activities with medical students. However, it could be interesting in much more knowledge fields.

This package contains different tools to add NLP capabilities for Lucene 4.x (it has been tested using Lucene version from 4.6.x to 4.8.1). Although it was originally developed for German, it is, mostly, language independent. It allows the user to lemmatize words to be indexed, to weight termy ba their parts of speech (e.g. weighting nouns mor hevaily than pronouns), and to add synonyms taken from GermaNet or a list you provide to the search index and thereby increase recall of lucene.

The semantic annotation system OPTIMA is the result of Andreas Vlachidis PhD work, (supervised by Prof. Douglas Tudhope, University of Glamorgan, UK). OPTIMA performs the NLP tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word Sense Disambiguation using hand-crafted rules and SKOS terminological resources (English Heritage Thesauri and Glossaries). The resulted semantic annotations are associated with classes of the (ISO 21127:2006) CIDOC Conceptual Reference Model (CRM) and its archaeological extension, CRM-EH. OPTIMA is also targeted at the detection and recognition of contextual relations between CRM entities. Such relations are modeled with respect to the CRM-EH archaeology extension. The pipeline targets the CIDOC-CRM entities; E19.Physical_Object, E53.Place, E49.Time_Appellation and E57.Material and the CRM-EH entities; EHE1001.Context_Event, EHE1002.Production_Event, EHE1004.Deposition_Event and P45.consists_of material property

TIES (Text Information Extraction System) is a clinical text search engine that uses Natural Language Processing techniques to extract medical concepts from free text clinical reports. It provides secure de-identified access to this information and has in built collaboration tools and honest broker functionality. It is licensed for academic use under the BSD license. For commercial use please contact Nexi at http://nexihub.com *** NOTICE: this software and forum are no longer maintained, as of 8/15/2019. You are free to continue to use this software under the license for academic use under the BSD license. For commercial use please contact Nexi at http://nexihub.com