Entity relationship-based feature construction method, device and equipment, and storage medium

A feature construction and entity relationship technology, applied in the field of big data, can solve problems such as the inability to express the characteristics of data in multiple dimensions

Pending Publication Date: 2020-07-28
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of this application is to provide a feature construction method, device, device, and storage medium based on entity relationships, ai

Method used

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  • Entity relationship-based feature construction method, device and equipment, and storage medium
  • Entity relationship-based feature construction method, device and equipment, and storage medium
  • Entity relationship-based feature construction method, device and equipment, and storage medium

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Embodiment Construction

[0063] It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0064] The present application provides a feature construction device based on entity relationship.

[0065] refer to figure 1 , figure 1 A schematic structural diagram of a device operating environment is constructed for the entity relationship-based features involved in the solution of the embodiment of the present application.

[0066] Such as figure 1 As shown, the entity relationship-based feature construction device includes: a processor 1001 , such as a CPU, a communication bus 1002 , a user interface 1003 , a network interface 1004 , and a memory 1005 . Wherein, the communication bus 1002 is used to realize connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard), and the network interface 1004 ...

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Abstract

The invention discloses an entity relationship-based feature construction method, and the method comprises the steps: obtaining a main table in a relational database and a plurality of auxiliary tables associated with the main table, enabling the main table to be provided with a main key column and a plurality of external key columns, enabling each entry in the main table to correspond to one entity, and enabling the auxiliary tables to be associated with the main table through external keys of the main table; constructing a directed inter-table relational graph by taking the main table and the auxiliary table as nodes and taking the incidence relation between every two of the main table and the auxiliary table as an edge; taking a node corresponding to the main table as a starting point,and traversing the inter-table relation graph to acquire inter-table relation data of each entity in the main table and the corresponding auxiliary table; and performing conversion calculation on theinter-table relationship data based on a preset conversion function to construct features corresponding to each entity in the main table. The invention further discloses a feature construction deviceand equipment based on the entity relationship and a storage medium. According to the method, the feature data is acquired based on the inter-table relational graph, and the features of the data can be represented from multiple dimensions on the whole, so that the modeling success rate is improved.

Description

technical field [0001] The present application relates to the field of big data technology, and in particular to a feature construction method, device, device and storage medium based on entity relationship. Background technique [0002] Feature engineering is the most time-consuming and energy-intensive part of data analysis. It is not a definite step like algorithms and models, but more engineering experience and trade-offs, so there is no unified method. Feature construction is an important part of feature engineering, which refers to constructing new features from original data, so that some physically meaningful features can be found from the original data. Assuming that the original data is tabular data, it is common to use mixed or combined attributes to create features, or decompose or split the original features to create features. [0003] Existing feature construction usually requires the help of forward or backward associations between data tables, and then perf...

Claims

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Application Information

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IPC IPC(8): G06F16/28G06F16/36
CPCG06F16/288G06F16/367
Inventor 刘利
Owner PING AN TECH (SHENZHEN) CO LTD
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