Name
Abstract | ||
|---|---|---|
Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background
of using Fuzzy language field and Fuzzy language values structure as description framework , the generalized cell Automation
that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is
brought forward. On this basis, the paper provides a kind of the new methods that can discover causal association rules. According
to the causal information of Standard Sample Space and Commonly Sample Space,through constructing its state (abnormality)
relation matrix, causal association rules can be gained by using inductive reasoning mechanism.The estimate of this algorithm
complexity is given,and its validity is proved through case.
|
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74205-0_40 | ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence |
Keywords | Field | DocType |
fuzzy language field,new method,inductive reasoning mechanism,generalized cell automation,language field,fuzzy language values structure,standard sample space,causal association rule,knowledge system,causal information,commonly sample space,causal association rule mining,generalized inductive logic causal,association rule,association rule mining,knowledge systems,inductive reasoning,causal models | Inductive reasoning,Logical matrix,Computer science,Fuzzy logic,Automation,Association rule learning,Knowledge extraction,Artificial intelligence,Sample space,Machine learning,Causal model | Conference |
Volume | Issue | ISSN |
4682 LNAI | null | 16113349 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai-jian Liang | 1 | 1 | 1.06 |
| Quan Liang | 2 | 22 | 2.42 |
| Bingru Yang | 3 | 186 | 26.67 |