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PODC
2006
ACM
15 years 11 months ago
Sketching asynchronous streams over a sliding window
We study the problem of maintaining sketches of recent elements of a data stream. Motivated by applications involving network data, we consider streams that are asynchronous, in w...
Srikanta Tirthapura, Bojian Xu, Costas Busch
KDD
2009
ACM
260views Data Mining» more  KDD 2009»
16 years 6 months ago
Enabling analysts in managed services for CRM analytics
Data analytics tools and frameworks abound, yet rapid deployment of analytics solutions that deliver actionable insights from business data remains a challenge. The primary reason...
Indrajit Bhattacharya, Shantanu Godbole, Ajay Gupt...
KDD
2002
ACM
293views Data Mining» more  KDD 2002»
16 years 5 months ago
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
Alexander Ypma, Tom Heskes
ICDM
2006
IEEE
91views Data Mining» more  ICDM 2006»
15 years 11 months ago
Entropy-based Concept Shift Detection
When monitoring sensory data (e.g., from a wearable device) the context oftentimes changes abruptly: people move from one situation (e.g., working quietly in their office) to ano...
Peter Vorburger, Abraham Bernstein
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
15 years 10 months ago
Issues in evaluation of stream learning algorithms
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...
João Gama, Raquel Sebastião, Pedro P...