@inproceedings{dangendorf-etal-2026-extracting,
    title = "Extracting Multi-Word Expressions Representing Technical Terms and Proper Nouns in Log Messages",
    author = {Dangendorf, Kilian  and
      H{\"a}nsel, Sven-Ove  and
      Rosendahl, Jannik  and
      Heine, Felix  and
      Kleiner, Carsten  and
      Wartena, Christian},
    editor = {Ojha, Atul Kr.  and
      Mititelu, Verginica Barbu  and
      Constant, Mathieu  and
      Stoyanova, Ivelina  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Rademaker, Alexandre},
    booktitle = "Proceedings of the 22nd Workshop on Multiword Expressions ({MWE} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Marocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.mwe-1.7/",
    pages = "61--65",
    ISBN = "979-8-89176-363-0",
    abstract = "IT-systems generate log messages containing important information about the system{'}s health. To gather information about system entities, we extract technical terms and proper nouns as multi-word expressions (MWEs) from a wide range of log messages from 16 different real systems. We apply Gries' information-theoretic approach which iteratively calculates the best MWE candidates using an eight-dimensional ranking method. These candidates are evaluated in an annotation study, achieving a precision of 66 {\%}. This value is significantly higher than evaluations on general-purpose texts, demonstrating the higher occurrence of compound technical terms and proper nouns in log messages. The MWEs found can be used to reduce the number of nodes in a system behavior graph while increasing the information density of the nodes."
}