Speed-up of a Knowledge-Based Clinical Diagnosis System using Reflexive Ontologies

被引：3

作者：

Artetxe, Arkaitz ^{[1
,4
]}

Sanchez, Eider ^{[1
,4
]}

Toro, Carlos ^{[1
]}

Sanin, Cesar ^{[2
]}

Szczerbicki, Edward ^{[2
]}

Grana, Manuel ^{[3
]}

Posada, Jorge ^{[1
]}

机构：

[1] Vicomtech IK4 Res Ctr, Mikeletegi Pasealekua 57, San Sebastian 20009, Spain

[2] Univ Newcastle, Fac Engn, Built Environ, Callaghan, NSW, Australia

[3] Univ Basque Country UPV EHU, San Sebastian, Spain

[4] Biodonostia Hlth Res Inst, Hlth Grp, San Sebastian, Spain

来源：

ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS | 2012年 / 243卷

关键词：

Knowledge Engineering; Reflexive Ontologies; Evaluation; Knowledge-Based System;

D O I：

10.3233/978-1-61499-105-2-1480

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Most of the time expended during ontology processing is derived from query actions. Quasi-real time goals require new approaches towards time efficiency (e.g. an intensively consumed application that pulls knowledge from an ontology). Reflexive Ontologies are a recent approach that is intended to bridge some of the aforementioned time consumption issues. In this paper we present an implementation of the Reflexive Ontologies in a knowledge-based Clinical Decision Support System for the diagnosis of Alzheimer's Disease. Our implementation is evaluated in order to show the impact of the application of reflexivity in the context described above. We give implementation details, as well as the definition of the evaluation methodology and evaluation results. Lastly performance improvements and some highlights of the application are also discussed.

引用

页码：1480 / 1489

页数：10

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