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A markov prediction model for data-driven semi-structured business processes · Study

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A markov prediction model for data-driven semi-structured business processes

Geetika T. Lakshmanan, Davood Shamsi, Y.N. Doganata, Merve Unuvar, Rania Y. Khalaf

2013-10-16articleKnowledge and Information Systems120 citationsclosed

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Business Process Modeling and Analysis AI-based Problem Solving and Planning Robotic Process Automation Applications

Abstract

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Citations in this library

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References

2011Process Mining: Discovery, Conformance and Enhancement of Business Processes

2003Workflow mining: A survey of issues and approaches

1998Discovering models of software processes from event-based data

2006Business process mining: An industrial application

2004Case handling: a new paradigm for business process support

2003Business Process Intelligence

2010Time prediction based on process mining

2006Decision Mining in ProM

Cited by

2017LSTM networks for data-aware remaining time prediction of business process instances

2017A Deep Learning Approach for Predicting Process Behaviour at Runtime

2018A Novel Business Process Prediction Model Using a Deep Learning Method

2014Data-aware remaining time prediction of business process instances

2021A Multi-View Deep Learning Approach for Predictive Business Process Monitoring

2020An extended model for remaining time prediction in manufacturing systems using process mining

2014A General Framework for Correlating Business Process Characteristics

2017A Multi-stage Deep Learning Approach for Business Process Event Prediction

Details

Year2013

Typearticle

VenueKnowledge and Information Systems

Languageen

Files0 public / 0

Identifiers

doi10.1007/s10115-013-0697-8

openalex_workW1998640084

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