FastContext is an optimized Java implementation of ConText algorithm (https://www.ncbi.nlm.nih.gov/pubmed/23920642). It runs two orders of magnitude faster and more accurate than previous two popluar implementations: JavaConText and GeneralConText.
<dependency>
<groupId>edu.utah.bmi.nlp</groupId>
<artifactId>fastcontext</artifactId>
<version>1.3.1.9</version>
</dependency>Note: the maven distribution doesn't include the context rule file, you can download it here if needed.
// Initiate FastContext
FastContext fc = new FastContext("conf/context.csv");
String inputString = "The patient denied any fever , although he complained some headache .";
ArrayList<Span> sent = SimpleParser.tokenizeOnWhitespaces(inputString);
LinkedHashMap<String, ConTextSpan> matches = fc.getFullContextFeatures("Concept", sent, 4, 4, inputString);
// To find the context information of "fever"For more detailed API uses, please refer to TestFastContextAPIs.java
Special thanks to Olga Patterson and Guy Divita for contributing rules as part of the context rule set.
If you are using FastContext within your research work, please cite the following publication:
Shi, Jianlin, and John F. Hurdle. “Trie-Based Rule Processing for Clinical NLP: A Use-Case Study of n-Trie, Making the ConText Algorithm More Efficient and Scalable.” Journal of Biomedical Informatics, August 6, 2018. https://doi.org/10.1016/j.jbi.2018.08.002.
Full text are available at: https://www.sciencedirect.com/science/article/pii/S1532046418301576
Preprint: https://arxiv.org/abs/1905.00079
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