Name
Abstract | ||
|---|---|---|
It is generally accepted that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are suitable, well-known logics for managing structured knowledge that have gained considerable attention the last decade. The current research progress and the existing problems of uncertain or imprecise knowledge representation and reasoning in DLs are analyzed in this paper. An integration between the theories of fuzzy DLs and rough DLs has been attempted by providing fuzzy rough DLs based on fuzzy rough set theory. The syntax, semantics and properties of fuzzy rough DLs are given. It is proved that the satisfiability, subsumption, entailment and ABox consistency reasoning in fuzzy rough DLs may be reduced to the ABox consistency reasoning in the corresponding fuzzy DLs. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.fss.2009.01.004 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
expressive fuzzy rough description,corresponding fuzzy dls,structured knowledge,fuzzy rough dls,imprecise knowledge representation,considerable attention,fuzzy rough set theory,rough dls,abox consistency reasoning,description logics,fuzzy dls,knowledge base,description logic,rough set theory,satisfiability,knowledge representation and reasoning | Discrete mathematics,Set theory,T-norm fuzzy logics,Knowledge representation and reasoning,Fuzzy logic,Abox,Description logic,Fuzzy set,Artificial intelligence,Fuzzy control system,Mathematics | Journal |
Volume | Issue | ISSN |
160 | 23 | Fuzzy Sets and Systems |
Citations | PageRank | References |
13 | 0.60 | 53 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuncheng Jiang | 1 | 375 | 24.36 |
| Ju Wang | 2 | 172 | 12.45 |
| Peimin Deng | 3 | 45 | 2.79 |
| Suqin Tang | 4 | 143 | 7.77 |