Ontological and Practical Issues in Using a Description Logic to Represent Medical Concept Systems: Experience from GALEN

2006 ◽  
pp. 197-231 ◽  
Author(s):  
Alan Rector ◽  
Jeremy Rogers
Keyword(s):  
Description Logic ◽  
Medical Concept ◽  
Concept Systems

Medical Concept systems, lexicons and Natural Language Generation

1997 ◽  
pp. 398-401
Author(s):  
Judith C. Wagner ◽  
Christian Lovis ◽  
Robert H. Baud ◽  
Jean-Raoul Scherrer
Keyword(s):  
Natural Language ◽  
Natural Language Generation ◽  
Language Generation ◽  
Medical Concept ◽  
Concept Systems

Deciding Query Entailment for Fuzzy Description Logic Knowledge Bases：The f-SH Family

2012 ◽  
Vol 35 (4) ◽  
pp. 767-785
Author(s):  
Jing-Wei CHENG ◽  
Zong-Min MA ◽  
Li YAN ◽  
Fu ZHANG
Keyword(s):  
Description Logic ◽  
Fuzzy Description

Semantics of OWL-S process model based on temporal description logic

2013 ◽  
Vol 33 (1) ◽  
pp. 266-269 ◽  
Author(s):  
Ming LI ◽  
Shiyi LIU ◽  
Fuzhong NIAN
Keyword(s):  
Process Model ◽  
Description Logic ◽  
Model Based

Syndication on the Web Using a Description Logic Approach

2008 ◽  
Author(s):  
Christian Halaschek-Wiener ◽  
Vladimir Kolovski
Keyword(s):  
Description Logic ◽  
Logic Approach ◽  
The Web

An Improved Set-based Reasoner for the Description Logic 𝒟ℒD4,׆

2021 ◽  
Vol 178 (4) ◽  
pp. 315-346
Author(s):  
Domenico Cantone ◽  
Marianna Nicolosi-Asmundo ◽  
Daniele Francesco Santamaria
Keyword(s):  
Semantic Web ◽  
Set Theory ◽  
Description Logic ◽  
Knowledge Bases ◽  
Query Answering ◽  
Conjunctive Query ◽  
Classification Problems ◽  
Previous Version ◽  
Decidable Fragment ◽  
Stratified Set

We present a KE-tableau-based implementation of a reasoner for a decidable fragment of (stratified) set theory expressing the description logic 𝒟ℒ〈4LQSR,×〉(D) (𝒟ℒD4,×, for short). Our application solves the main TBox and ABox reasoning problems for 𝒟ℒD4,×. In particular, it solves the consistency and the classification problems for 𝒟ℒD4,×-knowledge bases represented in set-theoretic terms, and a generalization of the Conjunctive Query Answering problem in which conjunctive queries with variables of three sorts are admitted. The reasoner, which extends and improves a previous version, is implemented in C++. It supports 𝒟ℒD4,×-knowledge bases serialized in the OWL/XML format and it admits also rules expressed in SWRL (Semantic Web Rule Language).

A Set-theoretic Approach to Reasoning Services for the Description Logic 𝒟 ℒ D 4,×

2020 ◽  
Vol 176 (3-4) ◽  
pp. 349-384
Author(s):  
Domenico Cantone ◽  
Marianna Nicolosi-Asmundo ◽  
Daniele Francesco Santamaria
Keyword(s):  
Description Logic ◽  
Description Logics ◽  
Theoretic Approach ◽  
The Novel ◽  
Data Types ◽  
Left Hand ◽  
Rule Languages ◽  
Tableau System ◽  
High Scalability ◽  
Better Than

In this paper we consider the most common TBox and ABox reasoning services for the description logic 𝒟ℒ〈4LQSR,x〉(D) ( 𝒟 ℒ D 4,× , for short) and prove their decidability via a reduction to the satisfiability problem for the set-theoretic fragment 4LQSR. 𝒟 ℒ D 4,× is a very expressive description logic. It combines the high scalability and efficiency of rule languages such as the SemanticWeb Rule Language (SWRL) with the expressivity of description logics. In fact, among other features, it supports Boolean operations on concepts and roles, role constructs such as the product of concepts and role chains on the left-hand side of inclusion axioms, role properties such as transitivity, symmetry, reflexivity, and irreflexivity, and data types. We further provide a KE-tableau-based procedure that allows one to reason on the main TBox and ABox reasoning tasks for the description logic 𝒟 ℒ D 4,× . Our algorithm is based on a variant of the KE-tableau system for sets of universally quantified clauses, where the KE-elimination rule is generalized in such a way as to incorporate the γ-rule. The novel system, called KEγ-tableau, turns out to be an improvement of the system introduced in [1] and of standard first-order KE-tableaux [2]. Suitable benchmark test sets executed on C++ implementations of the three mentioned systems show that in several cases the performances of the KEγ-tableau-based reasoner are up to about 400% better than the ones of the other two systems.

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