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Termin (Alle Termine)
Datum Freitag, 21. Juli 2023
Uhrzeit 11:30 – 12:00 Uhr (Dauer: 30 min)
Ort Raum 348 (Gebäude 50.34)
Vorheriger Termin Fr 14. Juli 2023
Nächster Termin Fr 18. August 2023

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Vortragende(r) Vincenzo Pace
Titel Attention Based Selection of Log Templates for Automatic Log Analysis
Vortragstyp Bachelorarbeit
Betreuer(in) Pawel Bielski
Vortragsmodus in Präsenz
Kurzfassung Log analysis serves as a crucial preprocessing step in text log data analysis, including anomaly detection in cloud system monitoring. However, selecting an optimal log parsing algorithm tailored to a specific task remains problematic.

With many algorithms to choose from, each requiring proper parameterization, making an informed decision becomes difficult. Moreover, the selected algorithm is typically applied uniformly across the entire dataset, regardless of the specific data analysis task, often leading to suboptimal results.

In this thesis, we evaluate a novel attention-based method for automating the selection of log parsing algorithms, aiming to improve data analysis outcomes. We build on the success of a recent Master Thesis, which introduced this attention-based method and demonstrated its promising results for a specific log parsing algorithm and dataset. The primary objective of our work is to evaluate the effectiveness of this approach across different algorithms and datasets.

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