RIS ID
75332
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. (C) 2012 Elsevier Ltd. All rights reserved.
Grant Number
ARC/DP0878172
Publication Details
Beydoun, G., Garcia-Sanchez, F., Vincent-Torres, C. M., Lopez-Lorca, A. A. & martinez-Bejar, R. (2013). Providing metrics and automatic enhancement for hierarchical taxonomies. Information Processing & Management, 49 (1), 67-82.