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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 6 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
16 years 6 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
KDD
2009
ACM
159views Data Mining» more  KDD 2009»
16 years 6 months ago
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation
Effective diagnosis of Alzheimer's disease (AD), the most common type of dementia in elderly patients, is of primary importance in biomedical research. Recent studies have de...
Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Tere...
KDD
2009
ACM
211views Data Mining» more  KDD 2009»
16 years 6 months ago
Address standardization with latent semantic association
Address standardization is a very challenging task in data cleansing. To provide better customer relationship management and business intelligence for customer-oriented cooperates...
Honglei Guo, Huijia Zhu, Zhili Guo, Xiaoxun Zhang,...
MOBISYS
2009
ACM
16 years 6 months ago
A framework of energy efficient mobile sensing for automatic user state recognition
Urban sensing, participatory sensing, and user activity recognition can provide rich contextual information for mobile applications such as social networking and location-based se...
Yi Wang, Jialiu Lin, Murali Annavaram, Quinn Jacob...