Name
Abstract | ||
|---|---|---|
This paper proposes the integration of probabilistic data streams and relational database by using Bayesian networks that is one of the most famous techniques for expressing uncertain contexts. A Baysian network is expressed by the graphical model while relational data are expressed by relation. To integrate them we make the relational model as the unified model for its simplicity. A Bayesian network is modeled as an abstract data type in an object relational database, and we define signatures to extract a probabilistic relation from a Bayesian network. We provide a scheme to integrate a probabilistic relation and normal relations. To allow continual queries over streams for a Bayesian network, we introduce a new concept, lifespan. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/SAINT.2008.108 | SAINT |
Keywords | Field | DocType |
Bayes methods,relational databases,Bayesian networks,continual queries,probabilistic data streams,probabilistic relation,relational data | Data mining,Variable-order Bayesian network,Relational database,Computer science,Bayesian programming,Bayesian network,Graphical model,Relational model,Dynamic Bayesian network,Probabilistic database | Conference |
Citations | PageRank | References |
3 | 0.38 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hideyuki Kawashima | 1 | 79 | 19.63 |
| Ryo Sato | 2 | 4 | 3.18 |
| Hiroyuki Kitagawa | 3 | 1031 | 148.79 |