Name
Abstract | ||
|---|---|---|
This paper describes a conceptual and theoretical framework for the resolution of seemingly contradictory evidence for decision-making. Basic to this approach is the use of granulation provided by the categories obtained by ascending concept hierarchies. This process will be driven by the use of a criterion that represents the utility of granular categories to the user's decision making. The definition of complete and partial evidence resolution and their properties are developed, which permits the formulation of the concept of preponderance of evidence for the decision maker. Finally, we show some preliminary results on the concepts of strength and consensus measures to provide metrics of the goodness of the evidence resolution. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TFUZZ.2007.895966 | IEEE T. Fuzzy Systems |
Keywords | Field | DocType |
concept hierarchy,partial evidence resolution,contradictory evidence,granular category,theoretical framework,consensus measure,evidence resolution,preliminary result,concept hierarchies,decision maker,fuzzy set theory,fuzzy set,knowledge engineering,machine intelligence,data mining,generalization,databases,fuzzy sets | Fuzzy set,Artificial intelligence,Knowledge engineering,Hierarchy,Mathematics,Decision maker,Machine learning,Concept hierarchy | Journal |
Volume | Issue | ISSN |
16 | 2 | 1063-6706 |
Citations | PageRank | References |
4 | 0.55 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| F. E. Petry | 1 | 184 | 19.59 |
| Ronald R. Yager | 2 | 986 | 206.03 |