Introducing LUIMA: An Experiment in Legal Conceptual Retrieval of Vaccine Injury Decisions using a UIMA Type System and Tools, Matthias Grabmair, Kevin D. Ashley, Ran Chen, Preethi Sureshkumar, Chen Wang, Eric Nyberg and Vern R. Walker. In the Proceedings of the 15th International Conference on Artificial Intelligence & Law (ICAIL 2015), June 8-12, 2015, pp. 69-78 (ACM: New York, 2015).
This paper presents first results from a proof of feasibility experiment in conceptual legal document retrieval in a particular domain (involving vaccine injury compensation). The conceptual markup of documents is done automatically using LUIMA, a law-specific semantic extraction toolbox based on the UIMA framework. The system consists of modules for automatic sub-sentence level annotation, machine learning based sentence annotation, basic retrieval using Apache Lucene and a machine learning based re-ranking of retrieved documents. In a leave-one-out experiment on a limited corpus, the resulting rankings scored higher for most tested queries than baseline rankings created using a commercial full-text legal information system.