Context-Aware Predictive Process Monitoring: The Impact of News Sentiment View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-10-18

AUTHORS

Anton Yeshchenko , Fernando Durier , Kate Revoredo , Jan Mendling , Flavia Santoro

ABSTRACT

Predictive business process monitoring is concerned with forecasting how a process is likely to proceed, covering questions such as what is the next activity to expect and what is the remaining time until case completion. Process prediction typically builds on machine learning techniques that leverage past process execution data. A fundamental problem of a process prediction methods is the data acquisition. So far, research on predictive monitoring utilize data, which is internal to the process. In this paper, we present a novel approach of integrating the external context of the business processes into prediction methods. More specifically, we develop a technique that leverages the sentiments of online news for the task of remaining time prediction. Using our prototypical implementation, we carried out experiments that demonstrate the usefulness of this approach and allowing us to draw conclusions about circumstances in which it works best. More... »

PAGES

586-603

Book

TITLE

On the Move to Meaningful Internet Systems. OTM 2018 Conferences

ISBN

978-3-030-02609-7
978-3-030-02610-3

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-02610-3_33

DOI

http://dx.doi.org/10.1007/978-3-030-02610-3_33

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107688530


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