Title of article
Providing metrics and automatic enhancement for hierarchical taxonomies
Author/Authors
Ghassan Beydoun، نويسنده , , Francisco Garc?a-S?nchez، نويسنده , , Cristin M. Vincent-Torres، نويسنده , , Antonio A. Lopez-Lorca، نويسنده , , Rodrigo Mart?nez-Béjar، نويسنده ,
Issue Information
دوماهنامه با شماره پیاپی سال 2013
Pages
16
From page
67
To page
82
Abstract
Taxonomies enable organising information in a human–machine understandable form, but constructing them for reuse and maintainability remains difficult. The paper presents a formal underpinning to provide quality metrics for a taxonomy under development. It proposes a methodology for semi-automatic building of maintainable taxonomies and outlines key features of the knowledge engineering context where the metrics and methodology are most suitable. The strength of the approach presented is that it is applied during the actual construction of the taxonomy. Users provide terms to describe different domain elements, as well as their attributes, and methodology uses metrics to assess the quality of this input. Changes according to given quality constraints are then proposed during the actual development of the taxonomy.
Keywords
Incremental knowledge development , Ontology Evaluation , Taxonomies , Data models , Knowledge monitoring
Journal title
Information Processing and Management
Serial Year
2013
Journal title
Information Processing and Management
Record number
1229328
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