Open AccessFLP : a feature‐based method for log parsing
Author(s) -
Zhong Ya,
Guo Yuanbo,
Liu Chunhui
Publication year - 2018
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2018.6079
Subject(s) - parsing , computer science , feature (linguistics) , binary logarithm , bottom up parsing , log log plot , artificial intelligence , scale (ratio) , data mining , algorithm , top down parsing , mathematics , discrete mathematics , philosophy , linguistics , physics , quantum mechanics
A feature‐based log parsing method is presented for extracting log events from unstructured free‐text logs. It is a data‐driven log analytic solution with no training data needed and suitable for various types of log parsing tasks. Experiments show that the proposed method can achieve higher accuracy and lower time complexity in large‐scale log data than existing log parsing methods.