111 search results - page 13 / 23 » Maintaining Stream Statistics over Sliding Windows |
101
click to vote
ISMIS
2009
Springer
15 years 7 months ago
2009
Springer
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
CIKM
2007
Springer
15 years 6 months ago
2007
Springer
In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...
117
Voted
ICDM
2007
IEEE
15 years 6 months ago
2007
IEEE
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
111
Voted
KDD
2009
ACM
15 years 5 months ago
2009
ACM
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
206
Voted
SIGMOD
2006
ACM
16 years 17 days ago
2006
ACM
In this paper, we present the design, implementation, and evaluation of a system that executes complex event queries over real-time streams of RFID readings encoded as events. The...