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» Improving Mining Quality by Exploiting Data Dependency
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INCDM
2010
Springer
204views Data Mining» more  INCDM 2010»
15 years 26 days ago
Combining Business Process and Data Discovery Techniques for Analyzing and Improving Integrated Care Pathways
Hospitals increasingly use process models for structuring their care processes. Activities performed to patients are logged to a database but these data are rarely used for managin...
Jonas Poelmans, Guido Dedene, Gerda Verheyden, Her...
85
Voted
VLDB
2001
ACM
100views Database» more  VLDB 2001»
15 years 1 months ago
Improving Business Process Quality through Exception Understanding, Prediction, and Prevention
Business process automation technologies are being increasingly used by many companies to improve the efficiency of both internal processes as well as of e-services offered to cus...
Daniela Grigori, Fabio Casati, Umeshwar Dayal, Min...
SDM
2009
SIAM
204views Data Mining» more  SDM 2009»
15 years 6 months ago
Application of Bayesian Partition Models in Warranty Data Analysis.
Automotive companies are forced to continuously extend and improve their product line-up. However, increasing diversity, higher design complexity, and shorter development cycles c...
Axel Blumenstock, Christoph Schlieder, Markus M&uu...
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
15 years 3 months ago
Spatial Multidimensional Sequence Clustering
Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measureme...
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se...
KDD
2004
ACM
163views Data Mining» more  KDD 2004»
15 years 10 months ago
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
William W. Cohen, Sunita Sarawagi