LEKG: A System for Constructing Knowledge Graphs from Log Extraction

Fangrong Wang, Alan Bundy, Xue Li, Ruiqi Zhu, Kwabena Nuamah, Lei Xu, Stefano Mauceri, Jeff Z. Pan*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Logs record system events and status, which help developers and system administrators diagnose run time errors, monitor running status and mine operation patterns [13, 23]. However, logs are complex and weakly linked, making it difficult to diagnose the causes of failures. While recent studies on log knowledge extraction focus on lifting entities from log messages for enriching a background knowledge graph (BKG), they do not involve knowledge reasoning for inferring implicit relations nor guarantee that the knowledge learned from log streams is consistent with the background knowledge. In this preliminary research paper, we present a log extraction approach to log knowledge graph (KG) construction. It includes a novel strategy that utilizes inference rules from a background knowledge graph to learn new triples and validate triples. Also, it implements a local to global strategy to perform reasoning on temporary log instance graphs (LIGs) then on the extended BKG, which significantly reduces query space. Finally we demonstrate the applicability of this approach by a use case in the context of root cause analysis.

Original languageEnglish
Title of host publicationProceedings of the 10th International Joint Conference on Knowledge Graphs, IJCKG 2021
EditorsOscar Corcho, Thepchai Supnithi, Xiaoyan Zhu, Aidan Hogan, Thanaruk Theeramunkong, Haofen Wang
PublisherAssociation for Computing Machinery, Inc
Number of pages5
ISBN (Electronic)9781450395656
Publication statusPublished - 6 Dec 2021
Event10th International Joint Conference on Knowledge Graphs, IJCKG 2021 - Virtual, Online, Thailand
Duration: 6 Dec 20218 Dec 2021


Conference10th International Joint Conference on Knowledge Graphs, IJCKG 2021
CityVirtual, Online


  • knowledge graph
  • log analysis
  • relation linking
  • root cause analysis

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