ONTOMETRIC: A Method to Choose the Appropriate Ontology
By Adolfo Lozano Tello, Asunción Gómez-Pérez. Journal of Database Management, 2004
450 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Management Information Systems
View Paper: https://www.semanticscholar.org/paper/d67d228d0f865aed51eb12f7474c9122a9542579
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- M. Suárez-Figueroa
- Carola Catenacci
- Massimiliano Ciaramita
- Jos Lehmann
- Aldo Gangemi
- Asunción Gómez-Pérez
- Ismailcem Budak Arpinar
- Enrico Motta
In Information Systems
- M. Suárez-Figueroa
- Carola Catenacci
- Massimiliano Ciaramita
- Jos Lehmann
- Aldo Gangemi
- Asunción Gómez-Pérez
- Enrico Motta
- Amit P. Sheth
In Management Information Systems
- Aldo Gangemi
- M. Suárez-Figueroa
- Enrico Motta
- Jos Lehmann
- Massimiliano Ciaramita
- Carola Catenacci
- Asunción Gómez-Pérez
- Amit P. Sheth
Citations in the corpus
- OntoQA: Metric-Based Ontology Quality Analysis (2005, background): “In [7], the authors propose a complex framework consisting of 160 characteristics spread across five dimensions: content of the ontology, language, development methodology, building tools, and usage costs.”
- Modelling Ontology Evaluation and Validation (2006, methodology): “OntoMetric ([14]) is an example of a tool that supports measurement based on a preferential ordering.”
- Ontology Engineering in a Networked World (2012, methodology): “Besides analytical activities, we conducted extensive literature research focused on theoretical methods (Pinto and Martins 2001; Gangemi et al. 1999; Lozano-Tello and Gómez-Pérez 2004) and also on case studies on reusing existing ontologies (Uschold et al.”