Abstract
The aim of this paper is to present a methodology for creating expert systems by processing texts in order to respond to the queries of a question answering system. In previous work, we have shown several algorithms that were able to extract causal information from text documents and to summarize it. These approaches extracted knowledge from unstructured information, but the performed representation could not be processed automatically to infer new knowledge. Generated summaries only present the information in natural language, and hence cannot be processed in order to generate complex implications. In this paper, we introduce a procedure capable of using this knowledge in order to infer new causal relations between concepts automatically by creating expert systems from the processed texts. These expert systems will contain the causal relations presented in the processed texts. In this representation, by using logic programming, we can infer new concepts that are implied by causal relations. We describe the methodology, technical details of the implementation of our question answering system and a full example where its usefulness is described.
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Acknowledgments
Work supported by the Spanish Ministry for Economy and Innovation and by the European Regional Development Fund (ERDF/FEDER) under grant TIN2016-76843-C4-2-R TIN2014-56633-C3-1-R and TIN2017-84796-C2-1-R, The authors acknowledge the use of the facilities of Centro de Computación Científica (CCC) at Universidad Autonoma de Madrid, and financial support from the Spanish Plan Nacional I+D+i, Grants TIN2016-76406-P and TEC2016-81900-REDT, and from Comunidad de Madrid, Grant S2013/ICE- 2845 CASI-CAM-CM.
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Garrido Merchán, E.C., Puente, C., Olivas, J.A. (2019). Generating a Question Answering System from Text Causal Relations. In: Pérez García, H., Sánchez González, L., Castejón Limas, M., Quintián Pardo, H., Corchado Rodríguez, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science(), vol 11734. Springer, Cham. https://doi.org/10.1007/978-3-030-29859-3_2
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