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ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
8 years 9 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
IJCAI
1989
9 years 1 months ago
Input Data Management in Real-Time AI Systems
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 reĀ­ ...
Richard Washington, Barbara Hayes-Roth
DEXA
2006
Springer
121views Database» more  DEXA 2006»
9 years 3 months ago
DCF: An Efficient Data Stream Clustering Framework for Streaming Applications
Streaming applications, such as environment monitoring and vehicle location tracking require handling high volumes of continuously arriving data and sudden fluctuations in these vo...
Kyungmin Cho, SungJae Jo, Hyukjae Jang, Su Myeon K...
MM
2005
ACM
153views Multimedia» more  MM 2005»
9 years 5 months ago
Body degree zero
alization is a combination of abstract generated forms and found imagery. The frequency, amplitude, and percentage differences between samples of incoming data are mapped to forms ...
Alan Dunning, Paul Woodrow, Morley Hollenberg
IDEAS
2006
IEEE
218views Database» more  IDEAS 2006»
9 years 5 months ago
PBIRCH: A Scalable Parallel Clustering algorithm for Incremental Data
We present a parallel version of BIRCH with the objective of enhancing the scalability without compromising on the quality of clustering. The incoming data is distributed in a cyc...
Ashwani Garg, Ashish Mangla, Neelima Gupta, Vasudh...
IPPS
2007
IEEE
9 years 6 months ago
Storage Optimization for Large-Scale Distributed Stream Processing Systems
We consider storage in an extremely large-scale distributed computer system designed for stream processing applications. In such systems, incoming data and intermediate results ma...
Kirsten Hildrum, Fred Douglis, Joel L. Wolf, Phili...
ICDM
2007
IEEE
158views Data Mining» more  ICDM 2007»
9 years 6 months ago
On Appropriate Assumptions to Mine Data Streams: Analysis and Practice
Recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. Somehow most existing work ma...
Jing Gao, Wei Fan, Jiawei Han
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