A SYSTEMIC METHODOLOGY FOR ONTOLOGY LEARNING An Academic Case Study and Evaluation

被引：0

作者：

Gil, Richard ^{[1
]}

Contreras, Leonardo ^{[1
]}

Martin-Bautista, Maria J. ^{[2
]}

机构：

[1] Univ Simon Bolivar, Dept Proc & Syst, Caracas, Venezuela

[2] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada, Spain

来源：

KEOD 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON KNOWLEDGE ENGINEERING AND ONTOLOGY DEVELOPMENT | 2010年

关键词：

Ontology Learning; Methodology; Systemic; Methodology Evaluation; Tools; Academic Domain; SEMANTIC WEB;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

There is an important dispersion of technical and methodological resources to support the complete Ontology Learning (OL) process from diverse knowledge sources. This fact makes the maintaining of the structures of representation (ontologies) difficult. Therefore, the Knowledge-based Systems associated with user's domains may not fulfil the increasing knowledge requirement from the user. In this paper, we give a possible solution for this problem. For this purpose, we propose a Systemic Methodology for OL (SMOL) that unifies and simplifies to the users the whole process of OL from different knowledge sources (ontologies, texts and databases). SMOL as methodology is evaluated under DESMET methods, in addition with their application for an academic case study is also included.

引用

页码：206 / 212

页数：7

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