18517425. PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA simplified abstract (Alipay (Hangzhou) Information Technology Co., Ltd.)
Contents
- 1 PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does this technology handle data privacy and security concerns?
- 1.11 What are the limitations of this technology in terms of scalability and complexity?
- 1.12 Original Abstract Submitted
PRIVACY-PROTECTING METHODS AND APPARATUSES FOR DETERMINING FEATURE EFFECTIVE VALUE OF BUSINESS DATA
Organization Name
Alipay (Hangzhou) Information Technology Co., Ltd.
Inventor(s)
Chaochao Chen 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.
