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» Using minimum description length for process mining
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DKE
2008
88views more  DKE 2008»
14 years 10 months ago
Quantifying process equivalence based on observed behavior
In various application domains there is a desire to compare process models, e.g., to relate an organization-specific process model to a reference model, to find a web service matc...
Ana Karla Alves de Medeiros, Wil M. P. van der Aal...
MLDM
2005
Springer
15 years 3 months ago
Multivariate Discretization by Recursive Supervised Bipartition of Graph
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Sylvain Ferrandiz, Marc Boullé
IJIIDS
2008
201views more  IJIIDS 2008»
14 years 10 months ago
MALEF: Framework for distributed machine learning and data mining
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...
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ICASSP
2011
IEEE
14 years 1 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
DATAMINE
2006
176views more  DATAMINE 2006»
14 years 10 months ago
A Bit Level Representation for Time Series Data Mining with Shape Based Similarity
Clipping is the process of transforming a real valued series into a sequence of bits representing whether each data is above or below the average. In this paper, we argue that clip...
Anthony J. Bagnall, Chotirat (Ann) Ratanamahatana,...