Method and device for jointly determining object feature correlation in private data by multiple parties

A technology for privacy data and object characteristics, which is applied in the field of data processing and can solve problems such as strong privacy protection requirements

Pending Publication Date: 2021-05-18
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the sample data in each platform often has strong privacy protection

Method used

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  • Method and device for jointly determining object feature correlation in private data by multiple parties
  • Method and device for jointly determining object feature correlation in private data by multiple parties
  • Method and device for jointly determining object feature correlation in private data by multiple parties

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Embodiment Construction

[0069] The solutions provided in this specification will be described below in conjunction with the accompanying drawings.

[0070] figure 1 It is a schematic diagram of an implementation scenario of an embodiment disclosed in this specification. Such as figure 1 As shown, in the shared learning scenario, the data set is jointly provided by multiple holders 1, 2, ..., M (M is a natural number), and each holder owns a part of the data in the data set, which constitutes the holder’s original matrix. The data set may be a training data set for training the neural network model, a test data set for testing the neural network model, or a data set to be predicted. The data set can include characteristic data of business objects, and the business objects can be objects to be analyzed in various businesses such as users, shops, commodities, and events.

[0071] There can be at least two data distributions here. One is that each holder has data of different characteristics of all ...

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Abstract

The embodiment of the invention provides a method and device for jointly determining object feature correlation in private data by multiple parties. The privacy data are distributed in a plurality of holders, and the first holder performs zero mean on feature values of multiple features in the first original matrix to obtain a first center matrix; and a first fragment matrix of the covariance matrix is determined based on the first central matrix and respective central matrixes of other owners by using multi-party security calculation. For the ith feature in the first holding party and the jth feature in the second holding party, the first holding party obtains data from the local covariance matrix fragment and the locally stored feature data, and determines a first correlation coefficient fragment between the ith feature and the jth feature based on the local feature data of the second holding party by using multi-party security calculation.

Description

technical field [0001] One or more embodiments of this specification relate to the technical field of data processing, and in particular to a method and device for multiple parties to jointly determine the correlation of object features in private data. Background technique [0002] In the process of constructing linear models in the real world, some sample features will be related to other sample features, that is, multicollinearity of features or variables, that is, there is a high correlation between sample features. When this situation is serious, it will increase the variance of the regression coefficient in the model, making the result of the regression model unstable. In the multi-platform joint modeling scenario, due to the joint modeling of multiple parties, the sample data used are generated in similar scenarios, which will inevitably produce collinear features with different names, so the correlation between features before building a linear model It is very nece...

Claims

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Application Information

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IPC IPC(8): G06F17/16G06F21/62
CPCG06F17/16G06F21/6245
Inventor 刘颖婷陈超超谭晋王力
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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