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KDD
2009
ACM
174views Data Mining» more  KDD 2009»
14 years 3 months ago
Handling outliers and concept drift in online mass flow prediction in CFB boilers
Jorn Bakker, Mykola Pechenizkiy, Indre Zliobaite, ...
KDD
2009
ACM
181views Data Mining» more  KDD 2009»
14 years 3 months ago
An exploration of climate data using complex networks
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
KDD
2009
ACM
170views Data Mining» more  KDD 2009»
14 years 3 months ago
Picture this: preferences for image search
Paul N. Bennett, David Maxwell Chickering, Anton M...
KDD
2009
ACM
168views Data Mining» more  KDD 2009»
14 years 3 months ago
CAPTCHA-based image labeling on the Soylent Grid
We introduce an open labeling platform for Computer Vision researchers based on Captchas, creating as a byproduct labeled image data sets while supporting web security. For the tw...
Peter Faymonville, Kai Wang, John Miller, Serge J....
KDD
2009
ACM
179views Data Mining» more  KDD 2009»
14 years 3 months ago
Identifying graphs from noisy and incomplete data
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
Galileo Mark S. Namata Jr., Lise Getoor
KDD
2009
ACM
205views Data Mining» more  KDD 2009»
14 years 3 months ago
From active towards InterActive learning: using consideration information to improve labeling correctness
Data mining techniques have become central to many applications. Most of those applications rely on so called supervised learning algorithms, which learn from given examples in th...
Abraham Bernstein, Jiwen Li
KDD
2009
ACM
298views Data Mining» more  KDD 2009»
14 years 3 months ago
Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, ...
Rong Pan, Martin Scholz
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 3 months ago
Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
Anomalous windows are the contiguous groupings of data points. In this paper, we propose an approach for discovering anomalous windows using Scan Statistics for Linear Intersectin...
Lei Shi, Vandana Pursnani Janeja
KDD
2009
ACM
129views Data Mining» more  KDD 2009»
14 years 3 months ago
Spatial-temporal causal modeling for climate change attribution
Aurelie C. Lozano, Hongfei Li, Alexandru Niculescu...