A Granular Space Model for Ontology Learning

Author

Qiu, Taorong ; Chen, Xiaoqing ; Liu, Qing ; Huang, Houkuan

Author_Institution

Beijing Jiaotong Univ., Beijing

fYear

2007

fDate

2-4 Nov. 2007

Firstpage

61

Lastpage

61

Abstract

Ontology learning technology has become a research hotspot in computer science nowadays. The main objective of this paper is to describe domain ontologies at different granularities and hierarchies based on granular computing. A granular space model for ontology learning was explored, and some definitions such as concept granules, granular worlds and the structure of granular space were described formally. Accordingly, the composition and decomposition of concept granules and operation properties were introduced. The proposed model is available for research on ontology learning and data mining at different levels of granularity based on granular computing.

Keywords

data mining; learning (artificial intelligence); ontologies (artificial intelligence); data mining; granular computing; granular space model; ontology learning technology; Astronomy; Computer science; Data mining; Information technology; Machine learning; Ontologies; Problem-solving; Set theory; Space technology; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Granular Computing, 2007. GRC 2007. IEEE International Conference on

Conference_Location

Fremont, CA

Print_ISBN

978-0-7695-3032-1

Type

conf

DOI

10.1109/GrC.2007.59

Filename

4403067