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KDD
2009
ACM
217views Data Mining» more  KDD 2009»
16 years 8 months ago
Efficient anomaly monitoring over moving object trajectory streams
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...
KDD
2009
ACM
141views Data Mining» more  KDD 2009»
16 years 8 months ago
Meme-tracking and the dynamics of the news cycle
Tracking new topics, ideas, and "memes" across the Web has been an issue of considerable interest. Recent work has developed methods for tracking topic shifts over long ...
Jure Leskovec, Lars Backstrom, Jon M. Kleinberg
193
Voted
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 8 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
16 years 7 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling
188
Voted
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
16 years 7 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
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