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KDD
2009
ACM
142views Data Mining» more  KDD 2009»
14 years 11 months ago
Quantification and semi-supervised classification methods for handling changes in class distribution
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
Jack Chongjie Xue, Gary M. Weiss
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 11 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
KDD
2009
ACM
143views Data Mining» more  KDD 2009»
14 years 11 months ago
Optimizing web traffic via the media scheduling problem
Website traffic varies through time in consistent and predictable ways, with highest traffic in the middle of the day. When providing media content to visitors, it is important to...
Lars Backstrom, Jon M. Kleinberg, Ravi Kumar
KDD
2009
ACM
170views Data Mining» more  KDD 2009»
14 years 11 months ago
Genre-based decomposition of email class noise
Corruption of data by class-label noise is an important practical concern impacting many classification problems. Studies of data cleaning techniques often assume a uniform label ...
Aleksander Kolcz, Gordon V. Cormack
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
14 years 11 months ago
Frequent pattern mining with uncertain data
In this paper, we will examine the frequent pattern mining for uncertain data sets. We will show how the broad classes of algorithms can be extended to the uncertain data setting....
Charu C. Aggarwal, Yan Li, Jianyong Wang, Jing Wan...
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
14 years 11 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
347views Data Mining» more  KDD 2009»
14 years 11 months ago
Network anomaly detection based on Eigen equation compression
This paper addresses the issue of unsupervised network anomaly detection. In recent years, networks have played more and more critical roles. Since their outages cause serious eco...
Shunsuke Hirose, Kenji Yamanishi, Takayuki Nakata,...
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 11 months ago
Analyzing patterns of user content generation in online social networks
Various online social networks (OSNs) have been developed rapidly on the Internet. Researchers have analyzed different properties of such OSNs, mainly focusing on the formation an...
Lei Guo, Enhua Tan, Songqing Chen, Xiaodong Zhang,...
KDD
2009
ACM
166views Data Mining» more  KDD 2009»
14 years 11 months ago
Measuring the effects of preprocessing decisions and network forces in dynamic network analysis
Social networks have become a major focus of research in recent years, initially directed towards static networks but increasingly, towards dynamic ones. In this paper, we investi...
Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfaha...
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 11 months ago
Characteristic relational patterns
Research in relational data mining has two major directions: finding global models of a relational database and the discovery of local relational patterns within a database. While...
Arne Koopman, Arno Siebes