Process Discovery Algorithms Using Numerical Abstract Domains
暂无分享,去创建一个
[1] Nicolas Halbwachs,et al. Automatic discovery of linear restraints among variables of a program , 1978, POPL.
[2] Josep Carmona,et al. Process Mining Meets Abstract Interpretation , 2010, ECML/PKDD.
[3] Chris H. Q. Ding,et al. K-means clustering via principal component analysis , 2004, ICML.
[4] Manuel Silva Suárez,et al. Petri Nets and Manufacturing Systems: An Examples-Driven Tour , 2003, Lectures on Concurrency and Petri Nets.
[5] Tadao Murata,et al. Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.
[6] Jianmin Wang,et al. Mining process models with non-free-choice constructs , 2007, Data Mining and Knowledge Discovery.
[7] Wil M. P. van der Aalst,et al. Conformance checking of processes based on monitoring real behavior , 2008, Inf. Syst..
[8] Jianmin Wang,et al. A novel approach for process mining based on event types , 2007, IEEE International Conference on Services Computing (SCC 2007).
[9] Haizhou Wang,et al. Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming , 2011, R J..
[10] Josep Carmona,et al. New Region-Based Algorithms for Deriving Bounded Petri Nets , 2010, IEEE Transactions on Computers.
[11] Roberto Bagnara,et al. Precise widening operators for convex polyhedra , 2003, Sci. Comput. Program..
[12] Robin Bergenthum,et al. Process Mining Based on Regions of Languages , 2007, BPM.
[13] A. J. M. M. Weijters,et al. Flexible Heuristics Miner (FHM) , 2011, 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).
[14] Goran Frehse,et al. PHAVer: algorithmic verification of hybrid systems past HyTech , 2005, International Journal on Software Tools for Technology Transfer.
[15] Manuel Silva Suárez,et al. Linear Algebraic and Linear Programming Techniques for the Analysis of Place or Transition Net Systems , 1996, Petri Nets.
[16] Wil M. P. van der Aalst,et al. Workflow mining: discovering process models from event logs , 2004, IEEE Transactions on Knowledge and Data Engineering.
[17] Josep Carmona,et al. Light Region-based Techniques for Process Discovery , 2011, Fundam. Informaticae.
[18] R. Tyrrell Rockafellar,et al. Convex Analysis , 1970, Princeton Landmarks in Mathematics and Physics.
[19] Patrick Cousot,et al. Static determination of dynamic properties of programs , 1976 .
[20] Antoine Miné,et al. The octagon abstract domain , 2001, High. Order Symb. Comput..
[21] Boudewijn F. van Dongen,et al. Process mining: a two-step approach to balance between underfitting and overfitting , 2008, Software & Systems Modeling.
[22] Pierre-Antoine Absil,et al. Principal Manifolds for Data Visualization and Dimension Reduction , 2007 .
[23] Emil Popescu,et al. On Galois Connexions , 1994 .
[24] Boudewijn F. van Dongen,et al. Process Discovery using Integer Linear Programming , 2009, Fundam. Informaticae.
[25] R. P. Jagadeesh Chandra Bose,et al. Process mining in the large : preprocessing, discovery, and diagnostics , 2012 .
[26] Ian T. Jolliffe,et al. Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.
[27] David Avis,et al. How good are convex hull algorithms? , 1995, SCG '95.
[28] Wil M. P. van der Aalst. Process mining , 2012, CACM.
[29] Andrzej Ehrenfeucht,et al. Partial (set) 2-structures , 1990, Acta Informatica.
[30] David Avis,et al. On canonical representations of convex polyhedra , 2002 .
[31] Patrick Cousot,et al. Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints , 1977, POPL.
[32] Wil M. P. van der Aalst,et al. Process Mining - Discovery, Conformance and Enhancement of Business Processes , 2011 .
[33] Bertrand Jeannet,et al. Apron: A Library of Numerical Abstract Domains for Static Analysis , 2009, CAV.
[34] Antoine Miné,et al. The octagon abstract domain , 2001, Proceedings Eighth Working Conference on Reverse Engineering.