Name
Abstract | ||
|---|---|---|
This paper addresses the problem of processing event-timing queries over event streams where the uncertainty in the values of the timestamps is characterizable by histograms. We describe a stream-partitioning technique for checking the satisfaction of a probabilistic timing constraint upon event arrivals in a systematic way in order to delimit the "probing range" in event streams. This technique can be formalized as a probabilistic timing join (PTJoin) operator where the join condition is specified by a time window and a confidence threshold in our model. We present efficient PTJoin algorithms that tightly delimit the probing range and efficiently invalidate events in event streams |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/RTCSA.2006.52 | Sydney, Qld. |
Keywords | Field | DocType |
database management systems,probability,query processing,confidence threshold,event-timing query processing,histogram,probabilistic timing join operator,probing range,stream-partitioning technique,time window,uncertain event stream | Histogram,Data mining,Computer science,Real-time computing,Timestamp,Operator (computer programming),Probabilistic logic,STREAMS | Conference |
ISSN | ISBN | Citations |
1533-2306 | 0-7695-2676-4 | 2 |
PageRank | References | Authors |
0.41 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aloysius K. Mok | 1 | 50 | 4.75 |
| Honguk Woo | 2 | 139 | 16.19 |
| Chan-Gun Lee | 3 | 19 | 1.34 |