Paper Info
Title
Representation and reasoning of context-dependant knowledge in distributed fuzzy ontologies
Abstract
Most of current knowledge based systems manage impressive amounts of information (especially distributed fuzzy information). In addition to widely pointed-out integration and maintenance difficulties, other common problem is overwhelming of users with much more information than the strictly necessary for fulfilling a task. This issue has been pointed out with the name of ''information overload''. Use of context knowledge has been envisioned as an appropriate solution to deal with this information overload matter. In this paper, we present a distributed fuzzy context-domain relevance (DFCDR) model for representation in fuzzy ontologies relevance relations between fuzzy context ontology and distributed fuzzy domain ontologies. In fact, the DFCDR model is a distributed fuzzy extension of the context-domain relevance (CDR) model.
Year
DOI
Venue
2010
10.1016/j.eswa.2010.02.122
Expert Syst. Appl.
Keywords
Field
DocType
distributed ontologies,context-aware systems,fuzzy ontologies relevance relation,information overload matter,fuzzy context-domain relevance,fuzzy extension,fuzzy information,dfcdr model,information overload,fuzzy domain ontology,context-dependant knowledge,knowledge representation and reasoning,context-domain relevance,fuzzy context ontology,description logics,fuzzy ontology,fuzzy ontologies,context dependent,description logic,knowledge based system
Ontology (information science),Ontology,Data mining,Information overload,Knowledge representation and reasoning,Computer science,Fuzzy logic,Description logic,Knowledge-based systems,Dependant
Journal
Volume
Issue
ISSN
37
8
Expert Systems With Applications
Citations 
PageRank 
References 
4
0.40
51
Authors
4
Name
Order
Citations
PageRank
Yuncheng Jiang137524.36
Yong Tang255476.46
Ju Wang317212.45
Suqin Tang41437.77