A kind of abnormal data processing method and system based on anti-counterfeiting traceability system
A technology of abnormal data and processing methods, applied in the field of anti-counterfeiting traceability, can solve the problems of the anti-counterfeiting traceability system being stopped, the inability to dig in-depth query results, and the inability of users to obtain the integrity of the intended consumer store. Real-time high effect
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Embodiment 1
[0047] A method for processing abnormal data based on an anti-counterfeit traceability system, comprising the following steps:
[0048] S1: Obtain user information and check the authenticity of the product;
[0049] S2: According to the obtained information, use data cleaning, data integration, data transformation and data reduction methods to preprocess the data;
[0050] S3: Perform anomaly detection on the data set to remove the interference of abnormal points;
[0051] S4: Use distance-based methods to find the most suspicious counterfeit sources for offline datasets; use frequency-based classification methods for online datasets to find the most suspicious counterfeit sources;
[0052] S5: Mark bad stores, and send the marked results to the database.
[0053] In step S1, the basic information, product information, query information and purchase route input by the user are received. The basic information includes ID, gender, age, product information includes price, type,...
Embodiment 2
[0073] Such as figure 2 As shown, an abnormal data processing system based on an anti-counterfeiting traceability system includes:
[0074] Information collection module 201: used to collect basic information input by users, product information, query information and purchase channels, basic information includes ID, gender, age, product information includes price, type, purpose, query information includes spatial location, time, purchase The channels are online and offline. For online purchases, you need to obtain a store ID;
[0075] Information preprocessing module 202: for preprocessing the data obtained by the information collection module to obtain a sample set D={x 1 ,x 2 ,...,x m}, containing m unlabeled samples, each sample x i =(x i1 ; x i2 ,...,x in ) is an n-dimensional feature vector, reflecting the feature information of counterfeit goods;
[0076] Anomaly detection module 203: used to perform anomaly detection on the preprocessed data and eliminate abnor...
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