ICTAI
2010
IEEE
13 years 2 months ago
2010
IEEE
Abstract--Pocket Data Mining PDM is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data stre...
PR
2007
13 years 4 months ago
2007
A data stream is a potentially uninterrupted flow of data. Mining this flow makes it necessary to cope with uncertainty, as only a part of the stream can be stored. In this pape...
JCST
2008
13 years 4 months ago
2008
Detecting duplicates in data streams is an important problem that has a wide range of applications. In general, precisely detecting duplicates in an unbounded data stream is not fe...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We consider the problem of extracting informative exemplars from a data stream. Examples of this problem include exemplarbased clustering and nonparametric inference such as Gauss...
COMAD
2009
13 years 5 months ago
2009
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
CIDR
2009
13 years 5 months ago
2009
High-volume, high-speed data streams may overwhelm the capabilities of stream processing systems; techniques such as data prioritization, avoidance of unnecessary processing and o...
CIDR
2009
13 years 5 months ago
2009
We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuse...
IJCAI
1989
13 years 5 months ago
1989
A real-time AI system in the real world needs to monitor an immense volume of data. To do this, the system must filter out much of the incoming data. However, it must remain re ...
SEBD
2003
13 years 6 months ago
2003
Abstract. Sensor networks represent a non traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Traditiona...
SDM
2003
SIAM
13 years 6 months ago
2003
SIAM
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...