Name
Abstract | ||
|---|---|---|
In many applications, uncertainty and ignorance go hand in hand. Therefore, to deliver database support for effective decision making, an integrated view of uncertainty and ignorance should be taken. So far, most of the efforts attempted to capture uncertainty and ignorance with probability theory. In this paper, we discuss the weakness to capture ignorance with probability theory, and propose an approach inspired by the Dempster-Shafer theory to capture uncertainty and ignorance. Then, we present a rule to combine dependent data that are represented in different relations. Such a rule is required to perform joins in a consistent way. We illustrate that our rule is able to solve the so-called problem of information loss, which was considered as an open problem so far. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11733836_23 | DASFAA |
Keywords | Field | DocType |
integrated view,dependent data,open problem,probability theory,information loss,database support,dempster-shafer theory,so-called problem,different relation,effective decision,dempster shafer theory | Data mining,Information loss,Joins,Open problem,Ignorance,Computer science,Decision support system,Artificial intelligence,Probability theory,Uncertainty handling,Dempster–Shafer theory,Database | Conference |
Volume | ISSN | ISBN |
3882 | 0302-9743 | 3-540-33337-1 |
Citations | PageRank | References |
7 | 0.68 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sunil Choenni | 1 | 309 | 111.82 |
| Henk Ernst Blok | 2 | 57 | 7.40 |
| Erik Leertouwer | 3 | 24 | 2.80 |