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KDD
2000
ACM
101views Data Mining» more  KDD 2000»
14 years 1 months ago
Incremental quantile estimation for massive tracking
Data--call records, internet packet headers, or other transaction records--are coming down a pipe at a ferocious rate, and we need to monitor statistics of the data. There is no r...
Fei Chen, Diane Lambert, José C. Pinheiro
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
14 years 1 months ago
A framework for specifying explicit bias for revision of approximate information extraction rules
Information extraction is one of the most important techniques used in Text Mining. One of the main problems in building information extraction (IE) systems is that the knowledge ...
Ronen Feldman, Yair Liberzon, Binyamin Rosenfeld, ...
KDD
2000
ACM
211views Data Mining» more  KDD 2000»
14 years 1 months ago
Mining IC test data to optimize VLSI testing
We describe an application of data mining and decision analysis to the problem of die-level functional test in integrated circuit manufacturing. Integrated circuits are fabricated...
Tony Fountain, Thomas G. Dietterich, Bill Sudyka
KDD
2000
ACM
81views Data Mining» more  KDD 2000»
14 years 1 months ago
Targeting the right students using data mining
The education domain offers a fertile ground for many interesting and challenging data mining applications. These applications can help both educators and students, and improve th...
Yiming Ma, Bing Liu, Ching Kian Wong, Philip S. Yu...
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
14 years 1 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar