Natural Language Engineering · 2014 · 124 citations · 24 references
ComputingComputer ScienceData MiningKnowledge RepresentationNatural Language ProcessingExpert SystemsInformation ExtractionKnowledge ExtractionRule-based RepresentationText MiningDomain Knowledge ExtractionRule ExtractionRule LanguagesRule MiningRule-based Knowledge RepresentationRule-based MatchingRule-based SystemsUnstructured Data Extraction
Abstract Rule-based information extraction is an important approach for processing the increasingly available amount of unstructured data. The manual creation of rule-based applications is a time-consuming and tedious task, which requires qualified knowledge engineers. The costs of this process can be reduced by providing a suitable rule language and extensive tooling support. This paper presents UIMA Ruta, a tool for rule-based information extraction and text processing applications. The system was designed with focus on rapid development. The rule language and its matching paradigm facilitate the quick specification of comprehensible extraction knowledge. They support a compact representation while still providing a high level of expressiveness. These advantages are supplemented by the development environment UIMA Ruta Workbench. It provides, in addition to extensive editing support, essential assistance for explanation of rule execution, introspection, automatic validation, and rule induction. UIMA Ruta is a useful tool for academia and industry due to its open source license. We compare UIMA Ruta to related rule-based systems especially concerning the compactness of the rule representation, the expressiveness, and the provided tooling support. The competitiveness of the runtime performance is shown in relation to a popular and freely-available system. A selection of case studies implemented with UIMA Ruta illustrates the usefulness of the system in real-world scenarios.
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Proceedings of the 24th international conference on Machine learning
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