Abstract
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.
| Original language | English |
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| 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 |
| Pages | 204-209 |
| 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 |
Publication series
| Series | CEUR Workshop Proceedings |
|---|---|
| Number | 2721 |
| ISSN | 1613-0073 |
Conference
| Conference | 19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020 |
|---|---|
| City | Virtual, Online |
| Period | 1/11/20 → 6/11/20 |
Bibliographical note
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