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Financial Knowledge Instantiation from Semi-structured, Heterogeneous Data Sources

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 764)

Abstract

Decision making in the financial domain is a very challenging endeavor. The risk associated to this process can be diminished by gathering as much accurate and pertinent information as possible. However, most relevant data currently lies over the Internet in heterogeneous sources. Semantic Web technologies have proven to be a useful means to integrate knowledge from disparate sources. In this work, a framework to semi-automatically populate ontologies from data in semi-structured documents is proposed. The validation results in the financial domain are very promising.

Keywords

  • Ontology population
  • Knowledge-based decision support system
  • Financial domain

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Acknowledgements

This work has been supported by the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER/ERDF) through project KBS4FIA (TIN2016-76323-R).

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Correspondence to Francisco García-Sánchez .

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García-Sánchez, F., García-Díaz, J.A., Gómez-Berbís, J.M., Valencia-García, R. (2019). Financial Knowledge Instantiation from Semi-structured, Heterogeneous Data Sources. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_11

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