Logs are a crucial source of information to diagnose the health and status of systems, but their manual investigation typically does not scale well and often leads to a lack of awareness and incomplete transparency about issues. To tackle this challenge, we introduce SLOGERT, a flexible framework and workflow for automated construction of knowledge graphs from arbitrary raw log messages. To this end, we combine a variety of techniques to facilitate a knowledge-based approach to log analysis.
|Title of host publication||Proceedings of the ISWC 2020 Demos and Industry Tracks: From Novel Ideas to Industrial Practice|
|Subtitle of host publication||co-located with 19th International Semantic Web Conference (ISWC 2020)|
|Editors||Kerry Taylor, Rafael Goncalves, Freddy Lecue, Jun Yan|
|Publisher||CEUR Workshop Proceedings|
|Publication status||Published - 2020|
|Event||19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020 - Virtual, Online|
Duration: 1 Nov 2020 → 6 Nov 2020
|Series||CEUR Workshop Proceedings|
|Conference||19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020|
|Period||1/11/20 → 6/11/20|
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