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KDD
2005
ACM
139views Data Mining» more  KDD 2005»
15 years 11 months ago
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Chunsheng Yang, Sylvain Létourneau
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
15 years 11 months ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu
VLDB
2005
ACM
140views Database» more  VLDB 2005»
15 years 11 months ago
Loadstar: Load Shedding in Data Stream Mining
In this demo, we show that intelligent load shedding is essential in achieving optimum results in mining data streams under various resource constraints. The Loadstar system intro...
Yun Chi, Haixun Wang, Philip S. Yu
VLDB
2005
ACM
196views Database» more  VLDB 2005»
15 years 11 months ago
Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
Graham Cormode, S. Muthukrishnan, Irina Rozenbaum
VLDB
2005
ACM
139views Database» more  VLDB 2005»
15 years 11 months ago
Statistical Learning Techniques for Costing XML Queries
Developing cost models for query optimization is significantly harder for XML queries than for traditional relational queries. The reason is that XML query operators are much mor...
Ning Zhang 0002, Peter J. Haas, Vanja Josifovski, ...
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