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» Approximate data mining in very large relational data
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KDD
2005
ACM
161views Data Mining» more  KDD 2005»
16 years 2 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
15 years 7 months ago
Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
Hyunjin Yoon, Cyrus Shahabi
VISUALIZATION
2002
IEEE
15 years 6 months ago
Interactive Rendering of Large Volume Data Sets
We present a new algorithm for rendering very large volume data sets at interactive framerates on standard PC hardware. The algorithm accepts scalar data sampled on a regular grid...
Stefan Guthe, Michael Wand, Julius Gonser, Wolfgan...
VLDB
2005
ACM
140views Database» more  VLDB 2005»
15 years 7 months ago
Loadstar: Load Shedding in Data Stream Mining
In this demo, we show that intelligent load shedding is essential in achieving optimum results in mining data streams under various resource constraints. The Loadstar system intro...
Yun Chi, Haixun Wang, Philip S. Yu
VLDB
1998
ACM
112views Database» more  VLDB 1998»
15 years 5 months ago
Incremental Clustering for Mining in a Data Warehousing Environment
Data warehouses provide a great deal of opportunities for performing data mining tasks such as classification and clustering. Typically, updates are collected and applied to the d...
Martin Ester, Hans-Peter Kriegel, Jörg Sander...