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Related Experiment Video

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Design and Optimization Strategies of a High-Performance Vented Box

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Published on: June 9, 2023

Optimizing the Most Specific Concept Method for Efficient Instance Checking.

Jia Xu, Patrick Shironoshita, Ubbo Visser

Proceedings of the ... International World-Wide Web Conference. International WWW Conference

|April 7, 2015

Summary

This summary is machine-generated.

We present an improved most specific concept (MSC) method for Description Logic (DL) SHI ontologies. This approach enhances data retrieval efficiency by converting instance checking into subsumption problems.

Keywords:

Algorithms Data retrieval Description Logic MSC Ontology SHI

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Area of Science:

Artificial Intelligence
Knowledge Representation and Reasoning

Background:

Instance checking is crucial for data retrieval in Description Logic (DL) ontologies.
Existing methods can be computationally intensive for large datasets.

Purpose of the Study:

To propose a revised most specific concept (MSC) method for DL SHI.
To enhance the efficiency of instance checking in DL ontologies.

Main Methods:

The revised MSC method converts instance checking into subsumption problems.
This allows for the generation of specific concepts tailored to queries.
Reasoning is optimized by exploring only relevant subsets of ABox data.

Main Results:

The proposed method generates smaller, more specific concepts.
Significant improvements in reasoning efficiency were observed.
Effectiveness demonstrated through concept size reduction and performance gains.

Conclusions:

The revised MSC method offers a more efficient approach to instance checking in DL SHI.
This contributes to faster and more scalable data retrieval from ontologies.