Text-aware predictive process monitoring with contextualized word embeddings

Cabrera Pérez L, Weinzierl S, Zilker S, Matzner M (2022)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2022

Pages Range: 1--12

Conference Proceedings Title: Proceedings of the BPM 2022 International Workshops

Event location: Münster

DOI: 10.1007/978-3-031-25383-6_22

Abstract

Predictive process monitoring (PPM) is the discipline of exploiting event logs of business processes to construct predictive models for anticipating different properties of running business processes. The event logs used contain control flow information of past process executions and, often, additional information about the context in which a process ran. As the process context can add valuable information to a predictive model, recent PPM techniques often incorporate it to improve process predictions. While most techniques incorporate context information as well-structured numerical and categorical context features, only a few utilize unstructured text from process-related comment fields, emails, or documents. The few existing text-aware PPM approaches are limited in capturing semantic information, as different meanings of the same word occurring in different contexts, i.e., sentences, are ignored. This paper addresses this limitation by proposing a text-aware PPM technique using contextualized word embeddings to predict the next activity and the next timestamp of running process instances. An experimental evaluation with a text-enriched real-life event log shows that our technique can outperform text-aware PPM approaches relying on non-contextualized word embeddings in terms of predictive performance.

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APA:

Cabrera Pérez, L., Weinzierl, S., Zilker, S., & Matzner, M. (2022). Text-aware predictive process monitoring with contextualized word embeddings. In Proceedings of the BPM 2022 International Workshops (pp. 1--12). Münster, DE.

MLA:

Cabrera Pérez, Lena, et al. "Text-aware predictive process monitoring with contextualized word embeddings." Proceedings of the International Conference on Business Process Management, Münster 2022. 1--12.

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