Attribution analysis method, electronic device, and storage medium
AssigneeDouyin Vision Co., Ltd.
InventorHao WANG
Life of this patent
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Abstract
The present disclosure provides an attribution analysis method, an electronic device, and a storage medium, wherein the method includes: acquiring target business data of an object to be analyzed, and acquiring a plurality of levels of data dimensions of the target business data; determining a target Trie tree based on the data dimensions and the target business data; determining a node contribution degree of each node in the target Trie tree based on the target business data; and performing an anomaly attribution analysis for the object to be analyzed based on the node contribution degree.
Claims20
An attribution analysis method, comprising:
- acquiring target business data of an object to be analyzed, and acquiring a plurality of levels of data dimensions of the target business data, wherein the data dimensions are associated with data types of the target business data;
- determining a target Trie tree based on the data dimensions and the target business data, wherein nodes at each level in the target Trie tree correspond to the data dimension at one level, and each node at individual levels is associated with the target business data belonging to the corresponding data dimension;
- determining a node contribution degree of each node in the target Trie tree based on the target business data, wherein the node contribution degree is used to indicate an impact of each node on a business indicator of the object to be analyzed;
- performing an anomaly attribution analysis for the object to be analyzed based on the node contribution degree.
An electronic device, comprising a processor, and a memory, the memory having machine-readable instructions executable by the processor stored thereon, wherein the machine-readable instructions, when executed by the processor, cause the electronic device to perform a method comprising:
- acquiring target business data of an object to be analyzed, and acquiring a plurality of levels of data dimensions of the target business data, wherein the data dimensions are associated with data types of the target business data;
- determining a target Trie tree based on the data dimensions and the target business data, wherein nodes at each level in the target Trie tree correspond to the data dimension at one level, and each node at individual levels is associated with the target business data belonging to the corresponding data dimension;
- determining a node contribution degree of each node in the target Trie tree based on the target business data, wherein the node contribution degree is used to indicate an impact of each node on a business indicator of the object to be analyzed;
- performing an anomaly attribution analysis for the object to be analyzed based on the node contribution degree.
A non-transitory computer-readable storage medium, the computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement a method comprising:
- acquiring target business data of an object to be analyzed, and acquiring a plurality of levels of data dimensions of the target business data, wherein the data dimensions are associated with data types of the target business data;
- determining a target Trie tree based on the data dimensions and the target business data, wherein nodes at each level in the target Trie tree correspond to the data dimension at one level, and each node at individual levels is associated with the target business data belonging to the corresponding data dimension;
- determining a node contribution degree of each node in the target Trie tree based on the target business data, wherein the node contribution degree is used to indicate an impact of each node on a business indicator of the object to be analyzed;
- performing an anomaly attribution analysis for the object to be analyzed based on the node contribution degree.
Dependencies are inferred from the claim text.