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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 6 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
IEAAIE
2009
Springer
14 years 17 days ago
Incremental Mining of Ontological Association Rules in Evolving Environments
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
Ming-Cheng Tseng, Wen-Yang Lin
AAAI
2008
13 years 8 months ago
Clustering on Complex Graphs
Complex graphs, in which multi-type nodes are linked to each other, frequently arise in many important applications, such as Web mining, information retrieval, bioinformatics, and...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu, Tian...
SIGSOFT
2007
ACM
14 years 6 months ago
Recommending random walks
We improve on previous recommender systems by taking advantage of the layered structure of software. We use a random-walk approach, mimicking the more focused behavior of a develo...
Zachary M. Saul, Vladimir Filkov, Premkumar T. Dev...
KDD
2009
ACM
160views Data Mining» more  KDD 2009»
14 years 24 days ago
Clustering event logs using iterative partitioning
The importance of event logs, as a source of information in systems and network management cannot be overemphasized. With the ever increasing size and complexity of today’s even...
Adetokunbo Makanju, A. Nur Zincir-Heywood, Evangel...