Granular computing applied to ontologies

@article{Calegari2010GranularCA,
  title={Granular computing applied to ontologies},
  author={Silvia Calegari and Davide Ciucci},
  journal={Int. J. Approx. Reasoning},
  year={2010},
  volume={51},
  pages={391-409}
}
Granular Computing is an emerging conceptual and computing paradigm of information processing. A central notion is an information-processing pyramid with different levels of clarifications. Each level is usually represented by ‘chunks’ of data or granules, also known as information granules. Rough Set Theory is one of the most widely used methodologies for handling or defining granules. Ontologies are used to represent the knowledge of a domain for specific applications. A challenge is to… CONTINUE READING
Highly Cited
This paper has 48 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 24 extracted citations

Data treatment from the viewpoint of granular computing

2017 IEEE International Conference on Big Data (Big Data) • 2017
View 1 Excerpt

Dynamic Updating Rough Approximations in Distributed Information Systems

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) • 2015
View 1 Excerpt

Parametric matroid of rough set

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems • 2015
View 1 Excerpt

Predicting freight with fuzzy granular computing and support vector machine model

2013 6th International Conference on Information Management, Innovation Management and Industrial Engineering • 2013
View 1 Excerpt

References

Publications referenced by this paper.
Showing 1-10 of 42 references

A Formal Theory of Granularity

View 7 Excerpts
Highly Influenced

A Granular Space Model for Ontology Learning

2007 IEEE International Conference on Granular Computing (GRC 2007) • 2007
View 5 Excerpts
Highly Influenced

A Translation Approach to Portable Ontology Specifications

T. Gruber
Knowledge Acquisition • 1993
View 7 Excerpts
Highly Influenced

Expressive probabilistic description logics

Artif. Intell. • 2008
View 4 Excerpts
Highly Influenced

Handling Missing Attribute Values

The Data Mining and Knowledge Discovery Handbook • 2005
View 4 Excerpts
Highly Influenced

The Evolution of Protégé: An Environment for Knowledge-Based Systems Development

M. A. Musen, R. W. Fergerson, +4 authors S. W. Tu
International Journal of Human-Computer Studies • 2003
View 6 Excerpts
Highly Influenced

Creating Semantic Web Contents with Protégé-2000

IEEE Intelligent Systems • 2001
View 4 Excerpts
Highly Influenced

Structured Writing with Granular Computing Strategies

2007 IEEE International Conference on Granular Computing (GRC 2007) • 2007
View 3 Excerpts
Highly Influenced

Sarca 314/16, I–20126 Milano (Italy) E-mail address: {calegari, ciucci}@disco.unimib.it

Bicocca, Viale
2012

Similar Papers

Loading similar papers…