Abnormal order portrait construction method based on big data

The invention relates to the technical field of big data analysis, in particular to an abnormal order portrait construction method based on big data, and the method comprises the steps: collecting a plurality of condition features triggered by a user side every a preset collection period, and calculating condition feature parameters corresponding to portrait tags; the method comprises the following steps: acquiring a plurality of portrait tags, determining whether the portrait tags and a plurality of condition features triggered by a user side are stored in a user portrait set corresponding to the user side or not, and determining tag types of the portrait tags in the user portrait set, and when the number ratio of the fuzzy portrait tags to the standard portrait tags in the user portrait set is higher than a preset ratio comparison threshold, determining that the portrait tags are stored in the user portrait set. According to the method, the relevance between each fuzzy portrait label and the standard portra