Mining EL Bases with Adaptable Role Depth

Authors

  • Ricardo Guimarães University of Bergen
  • Ana Ozaki University of Bergen
  • Cosimo Persia University of Bergen
  • Baris Sertkaya Frankfurt University of Applied Sciences

Keywords:

Description Logics, Knowledge Acquisition, Web Ontologies -- Creation, Extraction, Evolution

Abstract

In Formal Concept Analysis, a base for a finite structure is a set of implications that characterizes all valid implications of the structure. This notion can be adapted to the context of Description Logic, where the base consists of a set of concept inclusions instead of implications. In this setting, concept expressions can be arbitrarily large. Thus, it is not clear whether a finite base exists and, if so, how large concept expressions may need to be. We first revisit results in the literature for mining EL bases from finite interpretations. Those mainly focus on finding a finite base or on fixing the role depth but potentially losing some of the valid concept inclusions with higher role depth. We then present a new strategy for mining EL bases which is adaptable in the sense that it can bound the role depth of concepts depending on the local structure of the interpretation. Our strategy guarantees to capture all EL concept inclusions holding in the interpretation, not only the ones up to a fixed role depth.

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Published

2021-05-18

How to Cite

Guimarães, R., Ozaki, A., Persia, C., & Sertkaya, B. (2021). Mining EL Bases with Adaptable Role Depth. Proceedings of the AAAI Conference on Artificial Intelligence, 35(7), 6367-6374. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16790

Issue

Section

AAAI Technical Track on Knowledge Representation and Reasoning