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New framework enhances business process suffix prediction with decision mining

Researchers have developed a new framework for suffix prediction in business processes, enhancing the forecasting of remaining event sequences. This approach integrates decision mining with neural networks, creating a neuro-symbolic method that reasons about predicted events using mined decision rules. The framework aims to improve prediction accuracy, particularly for short prefixes and rare process variants, while also providing intrinsic interpretability. AI

IMPACT Introduces a novel neuro-symbolic approach to improve business process prediction and interpretability.

RANK_REASON The item is an academic paper published on arXiv detailing a new framework for business process analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New framework enhances business process suffix prediction with decision mining

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The item is an academic paper published on arXiv detailing a new framework for business process analysis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Henryk Mustroph, Stefanie Rinderle-Ma ·

    Decision-Aware Suffix Prediction and Reasoning of Business Processes

    arXiv:2609.06169v1 Announce Type: cross Abstract: Suffix prediction forecasts the remaining sequence of events of a running case until completion. Most approaches rely on neural networks trained on event logs, which, on average, perform well but struggle with short prefixes or ta…