Abstract: 【Purpose/significance】In order to accurately extract the method knowledge elements (KEs) in scientific literature and
achieve more granular knowledge organization and retrieval.【Method/process】This study proposes a rule-based method for extracting
method KEs in scientific literature. The method is divided into two stages: Semi-automated extraction stage of initial description rules
of method KEs and automated derivation and update stage of method KEs along with their additional description rules. The former
semi-automatically extracts initial method KEs based on the description characteristics of method KEs to get high-quality method
KEs, and summarizes the composition dimensions and initial description rules finally. This stage provides the data foundation for the
next stage, and also provides further insights into the composition dimensions of method KEs. The latter regards the initial rules as
clue words, and uses regular expressions to extract the method KEs from text, and then derives additional rules by the PreFixSpan algo⁃
rithm to supplement the initial rules.【Result/conclusion】In a preliminary evaluation on 16 papers, the P, R and F for the method KEs
extraction are 0.71, 0.80 and 0.73（>0.5）respectively, indicating the effectiveness of the method, and the method has certain reference
effect for more granular knowledge organization and retrieval.【Innovation/limitation】The limitation of the method lies in the need of
manual intervention in the extraction of the method knowledge elements description rules.