View source for 18517425. PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA simplified abstract (Alipay (Hangzhou) Information Technology Co., Ltd.)

=PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA=


==Organization Name==

[[:Category:Alipay (Hangzhou) Information Technology Co., Ltd.|Alipay (Hangzhou) Information Technology Co., Ltd.]]


[[Category:Alipay (Hangzhou) Information Technology Co., Ltd.]]

==Inventor(s)==

[[:Category:Yingting Liu of Hangzhou (CN)|Yingting Liu of Hangzhou (CN)]][[Category:Yingting Liu of Hangzhou (CN)]]

[[:Category:Chaochao Chen of Hangzhou (CN)|Chaochao Chen of Hangzhou (CN)]][[Category:Chaochao Chen of Hangzhou (CN)]]

[[:Category:Li Wang of Hangzhou (CN)|Li Wang of Hangzhou (CN)]][[Category:Li Wang of Hangzhou (CN)]]

==PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18517425 titled 'PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA

==Simplified Explanation==

The patent application describes a method for determining the effective value of a feature term in business data through secure multi-party computation and significance testing.

* Obtaining joint data share of a first participant based on joint data with feature values of objects and feature terms
* Obtaining predictive value share and model parameter share based on joint data and a business prediction model
* Determining correlation data share through secure multi-party computation
* Determining effective value of a feature term through a significance test method

== Potential Applications ==
This technology could be applied in various industries such as finance, marketing, and healthcare for analyzing and predicting business data effectively.

== Problems Solved ==
This technology solves the problem of accurately determining the value of specific feature terms in business data, leading to more informed decision-making and improved business strategies.

== Benefits ==
The benefits of this technology include enhanced data analysis capabilities, improved predictive modeling accuracy, and better understanding of the impact of different feature terms on business outcomes.

== Potential Commercial Applications ==
One potential commercial application of this technology could be in the development of advanced business intelligence tools for companies looking to optimize their data analysis processes.

== Possible Prior Art ==
One possible prior art could be the use of machine learning algorithms for feature selection and data analysis in business applications.

=== Unanswered Questions ===

== How does this technology handle data privacy and security concerns? ==
The patent application mentions secure multi-party computation, but it would be helpful to know more details about the specific security measures in place.

== What are the limitations of this technology in terms of scalability and complexity? ==
While the method described seems effective, it would be important to understand how it performs with larger datasets and more complex business scenarios.


==Original Abstract Submitted==

This specification discloses methods, apparatus, devices, and systems for determining a feature effective value of business data. In one implementation, a method includes: obtaining a joint data share of a first participant based on joint data that includes feature values of a plurality of objects corresponding to a plurality of feature terms, obtaining a predictive value share and a model parameter share based on the joint data and a business prediction model, determining, through secure multi-party computation, a correlation data share corresponding to the plurality of participants, and determining, through a significance test method, an effective value of a feature term of the plurality of feature terms.



[[Category:G06Q10/067]]
[[Category:G06F21/62]]