Name
Abstract | ||
|---|---|---|
Rough set theory is a useful tool for dealing with imprecise knowledge. One of the advantages of rough set theory is the fact that an unknown target concept can be approximately characterized by existing knowledge structures in a knowledge base. This paper explores knowledge structures in a knowledge base. Knowledge structures in a knowledge base are firstly described by means of set vectors and relationships between knowledge structures divided into four classes. Then, properties of knowledge structures are discussed. Finally, group, lattice, mapping, and soft characterizations of knowledge structures are given. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1111/exsy.12183 | Expert Systems |
Keywords | Field | DocType |
condition information amount,inclusion degree,knowledge base,knowledge structure,lattice,relation mapping | Data mining,Body of knowledge,Computer science,Knowledge-based systems,Rough set,Knowledge structure,Artificial intelligence,Knowledge base | Journal |
Volume | Issue | ISSN |
33 | 6 | 0266-4720 |
Citations | PageRank | References |
0 | 0.34 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhaowen Li | 1 | 50 | 4.47 |
| Qingguo Li | 2 | 435 | 44.53 |
| Rongrong Zhang | 3 | 0 | 0.34 |
| Ningxin Xie | 4 | 69 | 8.08 |