An SMT-Based Discovery Algorithm for C-Nets

Solé, Marc; Carmona, Josep

doi:10.1007/978-3-642-31131-4_4

Cited by 6 publications

(29 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it is a simple alternative to generate a model for sequences in which other approaches have problems in dealing with. We briefly describe the strategy to derive a C-net from a log based on Satisfiability Modulo Theories (SMT), presented in [7]. The approach is shown in Fig.…”

Section: Causal Nets (C-nets) and The Discovery Problemmentioning

confidence: 99%

“…The number of such obligations in ψ(β ←i ) can be computed by summing the number of times the obligation has been produced minus the number of times it has been already consumed before the execution of σ i . Since this equation is more involved than (E1) and (E2), please refer to [7] for the formal details.…”

Section: Logmentioning

confidence: 99%

“…To the best of our knowledge, the approach in [7] is the first algorithm for discovering the full class of C-nets. Remarkably, it offers two important guarantees: i) it derives a fitting model with ii) the minimal number of arcs.…”

Section: Introductionmentioning

confidence: 99%

“…The experiments performed in [8] show the capability of the high-level strategy to handle larger inputs. This paper presents a new application of the SMT-based approach from [7]. Instead of addressing discovery, it assumes an initial skeleton of a C-net (which can be obtained via discovery or manually), and amends the C-net in two dimensions: fitness and simplicity (see [1], Sect.…”

Section: Introductionmentioning

confidence: 99%

“…For fitness, it may incorporate new arcs and bindings necessary to reproduce the sequences in the log, while for simplicity it minimizes the number of arcs and bindings, removing the redundant ones. The core idea of the set of techniques of this paper strongly relies on adapting the SMT problem used for discovery in [7] to be used for simulation in this paper. One side-effect theoretical contribution of this paper is the reduction of the fitness decisional problem (i.e., does a C-net fit a log? )…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Amending C-net discovery algorithms

Solé

Carmona

2013

Proceedings of the 28th Annual ACM Symposium on Applied Computing

Self Cite

View full text Add to dashboard Cite

Abstract. As the complexity of information systems evolves, there is a growing interest in defining suitable process models than can overcome the limitations of traditional formalisms like Petri nets or related. Causal nets may be one of such promising process models, since important characteristics of their semantics deviate from the ones in the literature. Due to their novelty, very few discovery algorithms exist for Causal nets. Moreover, the existing ones offer very few guarantees regarding the outcome produced. This paper describes an algorithm that can be applied as a second step to any discovery technique to significantly improve the quality of the final Causal net derived. We have tested the technique in combination with the existing algorithms in the literature on several benchmarks, noticing a considerable improvement in all of them.

show abstract

Section: Causal Nets (C-nets) and The Discovery Problemmentioning

confidence: 99%

Section: Logmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Amending C-net discovery algorithms

Solé

Carmona

2013

Proceedings of the 28th Annual ACM Symposium on Applied Computing

Self Cite

View full text Add to dashboard Cite

show abstract

Process Mining

Leemans

2022

Lecture Notes in Business Information Processing

View full text Add to dashboard Cite

Encoding process discovery problems in SMT

Solé¹,

Carmona

2016

Softw Syst Model

Self Cite

View full text Add to dashboard Cite

Information systems, which are responsible for driving many processes in our lives (health care, the web, municipalities, commerce and business, among others), store information in the form of logs which is often left unused. Process mining, a discipline in between data mining and software engineering, proposes tailored algorithms to exploit the information stored in a log, in order to reason about the processes underlying an information system. A key challenge in process mining is discovery: Given a log, derive a formal process model that can be used afterward for a formal analysis. In this paper, we provide a general approach based on satisfiability modulo theories (SMT) as a solution for this challenging problem. By encoding the problem into the logical/arithmetic domains and using modern SMT engines, it is shown how two separate families of process models can be discovered. The theory of this paper is accompanied with a tool, and experimental results witness the significance of this novel view of the process discovery problem.

show abstract

An SMT-Based Discovery Algorithm for C-Nets

Cited by 6 publications

References 13 publications

Amending C-net discovery algorithms

Amending C-net discovery algorithms

Process Mining

Encoding process discovery problems in SMT

Contact Info

Product

Resources

About