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A Practical Approach for Scalable Conjunctive Query Answering on Acyclic \(\mathcal{EL}^+\) Knowledge Base

  • Jing Mei
  • Shengping Liu
  • Guotong Xie
  • Aditya Kalyanpur
  • Achille Fokoue
  • Yuan Ni
  • Hanyu Li
  • Yue Pan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5823)

Abstract

Conjunctive query answering for \(\mathcal{EL}^{++}\) ontologies has recently drawn much attention, as the Description Logic \(\mathcal{EL}^{++}\) captures the expressivity of many large ontologies in the biomedical domain and is the foundation for the OWL 2 EL profile. In this paper, we propose a practical approach for conjunctive query answering in a fragment of \(\mathcal{EL}^{++}\), namely acyclic \(\mathcal{EL}^+\), that supports role inclusions. This approach can be implemented with low cost by leveraging any existing relational database management system to do the ABox data completion and query answering. We conducted a preliminary experiment to evaluate our approach using a large clinical data set and show our approach is practical.

Keywords

Description Logic Conjunctive Query Query Answering Clinical Document Architecture Base Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jing Mei
    • 1
  • Shengping Liu
    • 1
  • Guotong Xie
    • 1
  • Aditya Kalyanpur
    • 2
  • Achille Fokoue
    • 2
  • Yuan Ni
    • 1
  • Hanyu Li
    • 1
  • Yue Pan
    • 1
  1. 1.IBM China Research LabBuilding 19 ZGC Software ParkBeijingChina
  2. 2.IBM Watson Research CenterYorktown HeightsUSA

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