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» Mining discriminative items in multiple data streams
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VLDB
2002
ACM
137views Database» more  VLDB 2002»
14 years 9 months ago
Comparing Data Streams Using Hamming Norms (How to Zero In)
Massive data streams are now fundamental to many data processing applications. For example, Internet routers produce large scale diagnostic data streams. Such streams are rarely s...
Graham Cormode, Mayur Datar, Piotr Indyk, S. Muthu...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 months ago
Real-time ranking with concept drift using expert advice
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
Hila Becker, Marta Arias
ECIR
2010
Springer
14 years 10 months ago
Aggregation of Multiple Judgments for Evaluating Ordered Lists
Abstract. Many tasks (e.g., search and summarization) result in an ordered list of items. In order to evaluate such an ordered list of items, we need to compare it with an ideal or...
Hyun Duk Kim, ChengXiang Zhai, Jiawei Han
101
Voted
SDM
2008
SIAM
118views Data Mining» more  SDM 2008»
14 years 11 months ago
Massive-Scale Kernel Discriminant Analysis: Mining for Quasars
We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...
Ryan Riegel, Alexander Gray, Gordon Richards
ICDE
2007
IEEE
167views Database» more  ICDE 2007»
15 years 4 months ago
Load Shedding for Window Joins on Multiple Data Streams
We consider the problem of semantic load shedding for continuous queries containing window joins on multiple data streams and propose a robust approach that is effective with the ...
Yan-Nei Law, Carlo Zaniolo