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Journal Articles Expert Systems with Applications Year : 2017

Xart: Discovery of correlated arguments of n-ary relations in text

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Abstract

Here we present the Xart system based on a three-step hybrid method using data mining approaches and syntactic analysis to automatically discover and extract relevant data modeled as n-ary relations in plain text. A n-ary relation links a studied object with its features considered as several arguments. We addressed the challenge of designing a novel method to handle the identification and extraction of het- erogeneous arguments such as symbolic arguments, quantitative arguments composed of numbers and various measurement units. We thus developed the Xart system, which relies on a domain ontology for discovering patterns, in plain text, to identify arguments involved in n-ary relations. The discovered pat- terns take advantage of different ontological levels that facilitate identification of all arguments and pool them in the sought n-ary relation.
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Dates and versions

hal-01508801 , version 1 (18-11-2019)

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Soumia Lilia Berrahou, Patrice Buche, Juliette Dibie-Barthelemy, Mathieu Roche. Xart: Discovery of correlated arguments of n-ary relations in text. Expert Systems with Applications, 2017, 73, pp.115-124. ⟨10.1016/j.eswa.2016.12.028⟩. ⟨hal-01508801⟩
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