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Self-adjusting Recommendations for People-Driven Ad-Hoc Processes · Study

WorkSelf-adjusting Recommendations for People-Driven Ad-Hoc Processes

Christoph Mayr‐Dorn2010

Work2010

Self-adjusting Recommendations for People-Driven Ad-Hoc Processes

Christoph Mayr‐Dorn · Thomas Burkhart · Dirk Werth · Schahram Dustdar

49 citations·0/0 files stored·Lecture notes in computer science

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Business Process Modeling and Analysis Usability and User Interface Design Recommender Systems and Techniques

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References

2008Business Process Management Workshops 2006A Declarative Approach for Flexible Business Processes Management 2004AgentWork: a workflow system supporting rule-based workflow adaptation 2007Constraint-Based Workflow Models: Change Made Easy 2001Pockets of Flexibility in Workflow Specification 2008Supporting Flexible Processes through Recommendations Based on History 2003Caramba—A Process-Aware Collaboration System Supporting Ad hoc and Collaborative Processes in Virtual Teams 2003The Case Handling Case

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2019Customer Purchase Intent Prediction Under Online Multi-Channel Promotion: A Feature-Combined Deep Learning Framework 2013A purchase decision-making process model of online consumers and its influential factor : a cross sector analysis 2013Enabling the Analysis of Cross-Cutting Aspects in Ad-Hoc Processes 2011Next Best Step and Expert Recommendation for Collaborative Processes in IT Service Management 2013Improving the process of process modelling by the use of domain process patterns

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Details

Year2010

Typeother

Published2010-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations49

Files0 public / 0

ShelfBusiness Process Modeling and Analysis

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doi10.1007/978-3-642-15618-2_23

openalex_workW1563307751

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2011

Predictive Analytics for Semi-structured Case Oriented Business Processes

2014A role model-based approach for modelling collaborative processes

2015Next step recommendation and prediction based on process mining in adaptive case management