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KDD
2009
ACM
223views Data Mining» more  KDD 2009»
16 years 5 months ago
Collaborative filtering with temporal dynamics
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are ...
Yehuda Koren
KDD
2009
ACM
232views Data Mining» more  KDD 2009»
16 years 5 months ago
Classification of software behaviors for failure detection: a discriminative pattern mining approach
Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs an...
David Lo, Hong Cheng, Jiawei Han, Siau-Cheng Khoo,...
173
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MOBISYS
2009
ACM
16 years 5 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...
KDD
2008
ACM
142views Data Mining» more  KDD 2008»
16 years 5 months ago
Efficient ticket routing by resolution sequence mining
IT problem management calls for quick identification of resolvers to reported problems. The efficiency of this process highly depends on ticket routing--transferring problem ticke...
Qihong Shao, Yi Chen, Shu Tao, Xifeng Yan, Nikos A...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 5 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
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