52 search results - page 2 / 11 » Novelty Detection from Evolving Complex Data Streams with Ti... |
ICDE
2008
IEEE
14 years 6 months ago
2008
IEEE
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
KDD
2009
ACM
13 years 10 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...
KDD
2003
ACM
14 years 5 months ago
2003
ACM
Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to mo...
CICLING
2010
Springer
14 years 5 days ago
2010
Springer
We present an approach for automatic detection of topic change. Our approach is based on the analysis of statistical features of topics in time-sliced corpora and their dynamics ov...
PODS
2010
ACM
13 years 10 months ago
2010
ACM
A fundamental problem in data management is to draw a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With large, streamin...