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Applying Ontology-Informed Lattice Reduction Using the Discrimination Power Index to Financial Domain

  • Qudamah QuboaEmail author
  • Nikolay Mehandjiev
  • Ali Behnaz
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 345)

Abstract

Contemporary financial institutions are relying on varied and voluminous data and so they need advanced technologies to provide their customers with the best possible services. Capturing the meaning, or semantics, of data and presenting these semantics in simplified yet relevant models are key challenges to achieving this. Formal Concept Analysis (FCA) automates the analysis of properties and instances of the data, generating a lattice which groups properties and instances into concepts. This lattice can be used as automatically generated semantic structure describing the domain, yet the complexity and size of the resultant lattice render this technique unusable in most practical cases involving financial data. To tackle this, our Ontology-informed Lattice Reduction approach can guide the reduction of the lattices generated from financial sampled data. We validate the adaptation of the approach to the financial domain through a real-world asset allocation case study, demonstrating that the approach achieves good overall performance and relevant results.

Keywords

FCA Semantic structures Lattice reduction Validation 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Alliance Manchester Business SchoolUniversity of ManchesterManchesterUK
  2. 2.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia

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