arXiv AI By Alessandro Mele, Claudia Diamantini, Domenico Potena

Leveraging contextual events on structure-aware next activity prediction

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arXiv Machine Learning
Jul 31

Revisiting Predictive Process Monitoring in the Age of Foundation Models: A Comparative Study of Sequence, Tabular, and LLM Approaches

arXiv:2607. 27797v1 Announce Type: new Abstract: Predictive process monitoring (PPM) leverages event logs to forecast the future of running process instances, for instance, predicting the next activity, the remaining time until case completion, or the time to the next event.

By Lennart Fertig, Lukas Kirchdorfer, Tobias Sesterhenn
arXiv Machine Learning
Sep 3

MISApp: Multi-Hop Intent-Aware Session Graph Learning for Next App Prediction

MISApp is a profile‑free framework that predicts the next mobile app a user will launch by learning multi‑hop session graphs. It captures transition dependencies across different structural ranges, incorporates temporal context and spatial categorization, and models intent evolution from recent interactions. Experiments on two real‑world datasets show MISApp outperforms baselines in both standard and cold‑start settings while remaining efficient, and analyses reveal that multi‑hop relations provide higher‑order predictive signals and interpretable attention weights.

By Yunchi Yang, Longlong Li, Jianliang Wu, Cunquan Qu