Name
Abstract | ||
|---|---|---|
We consider the problem of information fusion, specifically the task of fusing information from two different categories, information which is directly about an object of interest (OBJOIN information) and information about related objects (peer information). We discuss the representation of these different types of information, the first in terms of a possibilistic distribution and the second in terms of a probability distribution. We introduce an approach to information fusion based upon the use of the fuzzy modeling technology. In this approach we represent the fusion function in terms of rules which indicate when to use the different types of information. Particularly notable here is the role of information quality as a guiding factor in the fusion process. (C) 2001 John Wiley & Sons, Inc. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1002/int.1067 | INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS |
Field | DocType | Volume |
Information integration,Data mining,Fuzzy logic,Sensor fusion,Probability distribution,Artificial intelligence,Interaction information,Fuzzy control system,Mathematics,Machine learning,Information quality,Information filtering system | Journal | 16 |
Issue | ISSN | Citations |
12 | 0884-8173 | 2 |
PageRank | References | Authors |
0.47 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ronald R. Yager | 1 | 9852 | 1562.99 |
| Frederick E. Petry | 2 | 562 | 69.24 |