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Authors: Sébastien Salva ; Laurent Provot and Jarod Sue

Affiliation: LIMOS - UMR CNRS 6158, Clermont Auvergne University, Aubière, France

Keyword(s): Event Log, Session, Conversation Extraction, Correlation.

Abstract: Event logs are more and more considered for helping IT personnel understand system behaviour or performance. One way to get knowledge from event logs is by extracting conversations (a.k.a. sessions) through the recovering of event correlations. This paper proposes a highly parallel algorithm to retrieve conversations from event logs, without having any knowledge about the used correlation mechanisms. To make the event log exploration effective and efficient, we devised an algorithm that covers an event log and builds the possible conversation sets w.r.t. the data found within the events. To limit the conversation set exploration and quicker recover good candidates, the algorithm is guided by an heuristic based upon the evaluation of invariants and conversation quality attributes. This heuristic also offers flexibility to users, as the quality and invariants can be adapted to the system context. We report experimental results obtained from 6 case studies and show that our algorithm ha s the capability of recovering the expected conversation sets in reasonable time delays. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Salva, S.; Provot, L. and Sue, J. (2021). Conversation Extraction from Event Logs. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR; ISBN 978-989-758-533-3; ISSN 2184-3228, SciTePress, pages 155-163. DOI: 10.5220/0010652300003064

@conference{kdir21,
author={Sébastien Salva. and Laurent Provot. and Jarod Sue.},
title={Conversation Extraction from Event Logs},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR},
year={2021},
pages={155-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010652300003064},
isbn={978-989-758-533-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR
TI - Conversation Extraction from Event Logs
SN - 978-989-758-533-3
IS - 2184-3228
AU - Salva, S.
AU - Provot, L.
AU - Sue, J.
PY - 2021
SP - 155
EP - 163
DO - 10.5220/0010652300003064
PB - SciTePress