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» Information extraction, data mining and joint inference
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KDD
2008
ACM
128views Data Mining» more  KDD 2008»
15 years 10 months ago
Bypass rates: reducing query abandonment using negative inferences
We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed--documents returned higher in the ordering of the ...
Atish Das Sarma, Sreenivas Gollapudi, Samuel Ieong
CAISE
2005
Springer
15 years 3 months ago
A Meta Model for Process Mining Data
Abstract. Modern process-aware information systems store detailed information about processes as they are being executed. This kind of information can be used for very different p...
Boudewijn F. van Dongen, Wil M. P. van der Aalst
IIS
2004
14 years 11 months ago
Query Selectivity Estimation via Data Mining
Estimating the result size of a join is an important query optimization problem as it determines the choice of a good query evaluation strategy. Yet, there are few efficient techni...
Jarek Gryz, Dongming Liang
EDM
2009
184views Data Mining» more  EDM 2009»
14 years 7 months ago
Process Mining Online Assessment Data
Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated throug...
Mykola Pechenizkiy, Nikola Trcka, Ekaterina Vasily...
GI
1998
Springer
15 years 2 months ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller