Data processing method and data processing device
A data processing and sample data technology, applied in the computer field, can solve problems such as inaccurate data and lack of universality, and achieve the effect of improving efficiency and accuracy
Active Publication Date: 2021-05-14
TENCENT TECH (SHENZHEN) CO LTD
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In the existing scheme, manual intervention is required. Due to the subjectivity of manual intervention, the selected threshold varies from person to person. Manually selected thresholds are not universal in business scenarios with large data fluctuations.
Therefore, making the final screening data not accurate enough
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[0027] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.
[0028] In order to better understand the embodiments of the present application, the following introduces the technical terms involved in the embodiments of the present application:
[0029] Cluster Analysis: Cluster analysis refers to the analytical process of grouping a collection of physical or abstract objects into classes consisting of similar objects.
[0030] Anomaly Detection: I...
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The embodiment of the invention provides a data processing method and a data processing device, and is applied to the technical field of artificial intelligence. The method specifically comprises: obtaining a sample data set, wherein each group of sample data included in the sample data set is composed of annotation data and year-on-year data corresponding to the annotation data; performing clustering processing on the sample data in the sample data set to obtain a clustering processing result, wherein the clustering processing result is used for indicating a clustering category to which each group of sample data belongs; according to the clustering processing result, determining attribute parameters corresponding to the sample data belonging to a target clustering category, wherein the target clustering category is any clustering category meeting a specific condition in the clustering processing result; and according to the attribute parameters corresponding to each target clustering category, determining a target upper limit threshold and a target lower limit threshold corresponding to the sample data set, wherein the target upper limit threshold and the target lower limit threshold are used for screening abnormal data. According to the scheme, the efficiency and accuracy of selecting the upper limit threshold and the lower limit threshold can be improved.
Description
technical field [0001] The present application relates to the field of computer technology, in particular to a data processing method and a data processing device. Background technique [0002] Time series refers to the numerical sequence that arranges the values of the same statistical index according to the time sequence of their occurrence. Usually, analysis based on time series is suitable for big data business scenarios, and the subsequent analysis results of time series can be used for anomaly detection in big data business scenarios. [0003] At present, the method of anomaly detection for big data business scenarios is mainly to select thresholds based on manual experience, and to filter abnormal data based on the selected thresholds. In the existing solutions, manual intervention is required. Due to the subjectivity of manual intervention, the selected thresholds vary from person to person. Manually selected thresholds are not universal in business scenarios with...
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IPC IPC(8): G06F16/2458G06F16/28G06K9/62
CPCG06F16/2474G06F16/285G06F18/2321
Inventor 梅宇航尹堃周雪黄子超孔舟帆
Owner TENCENT TECH (SHENZHEN) CO LTD