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» Improving process models by discovering decision points
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EOR
2006
104views more  EOR 2006»
13 years 8 months ago
Link function selection in stochastic multicriteria decision making models
A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data model...
Eugene D. Hahn
ICCV
2011
IEEE
12 years 8 months ago
Discovering Object Instances from Scenes of Daily Living
We propose an approach to identify and segment objects from scenes that a person (or robot) encounters in Activities of Daily Living (ADL). Images collected in those cluttered sce...
Hongwen Kang, Martial Hebert, Takeo Kanade
HICSS
2007
IEEE
115views Biometrics» more  HICSS 2007»
14 years 2 months ago
Information losses within the collaborative integration of different process models - BPML as an XML-based interchange format fo
During the last decades market competition created various constellations of collaborative integration between enterprises: integration of parts of the value chain or integration ...
Johannsen Florian, Susanne Leist, Gregor Zellner
BMCBI
2010
142views more  BMCBI 2010»
13 years 8 months ago
Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity
Background: Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells...
Jongkwang Kim, Kai Tan
ICDM
2003
IEEE
92views Data Mining» more  ICDM 2003»
14 years 1 months ago
Postprocessing Decision Trees to Extract Actionable Knowledge
Most data mining algorithms and tools stop at discovered customer models, producing distribution information on customer profiles. Such techniques, when applied to industrial pro...
Qiang Yang, Jie Yin, Charles X. Ling, Tielin Chen