18437118. DATA PROCESSING METHOD AND APPARATUS, PROGRAM PRODUCT, COMPUTER DEVICE, AND MEDIUM simplified abstract (TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED)

DATA PROCESSING METHOD AND APPARATUS, PROGRAM PRODUCT, COMPUTER DEVICE, AND MEDIUM

Organization Name

TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor(s)

Chunxu Shen of Shenzhen (CN)

Kouying Xue of Shenzhen (CN)

Hao Cheng of Shenzhen (CN)

DATA PROCESSING METHOD AND APPARATUS, PROGRAM PRODUCT, COMPUTER DEVICE, AND MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18437118 titled 'DATA PROCESSING METHOD AND APPARATUS, PROGRAM PRODUCT, COMPUTER DEVICE, AND MEDIUM

Simplified Explanation

The patent application describes a data processing method using a computer device to predict a conversion index of an object for a resource based on a heterogeneous conversion graph, homogeneous object graph, and homogeneous resource graph.

• Obtaining a heterogeneous conversion graph with object nodes and resource nodes connected by edges representing conversion behaviors.
• Creating homogeneous object graphs for each object with feature nodes in multiple dimensions.
• Generating homogeneous resource graphs for each resource with feature nodes in multiple dimensions.
• Training a prediction network using the conversion graph, object graphs, and resource graphs to predict conversion indexes.

Potential Applications

This technology could be applied in various industries such as e-commerce, advertising, and recommendation systems to predict user behavior and optimize conversions.

Problems Solved

This technology solves the problem of accurately predicting conversion rates for specific objects and resources, allowing for targeted marketing strategies and personalized recommendations.

Benefits

The benefits of this technology include improved conversion rates, increased efficiency in marketing campaigns, and enhanced user experience through personalized recommendations.

Potential Commercial Applications

One potential commercial application of this technology could be in the e-commerce industry for predicting customer preferences and optimizing product recommendations to increase sales.

Possible Prior Art

One possible prior art for this technology could be machine learning algorithms used for recommendation systems in e-commerce platforms, but the specific method of training a prediction network based on heterogeneous and homogeneous graphs may be novel.

How does this technology handle data privacy and security concerns?

This article does not address how the data processing method ensures the privacy and security of user information when training the prediction network.

What are the computational requirements for implementing this technology at scale?

The article does not provide information on the computational resources needed to train and deploy the prediction network for large datasets or real-time applications.

Original Abstract Submitted

This application discloses a data processing method performed by a computer device, and the method includes: obtaining a heterogeneous conversion graph including N object nodes and M resource nodes, when an object has a conversion behavior for a resource, a connecting edge exists between a corresponding object node and a corresponding resource node; obtaining a homogeneous object graph corresponding to each object, the graph including object feature nodes of the corresponding object in a plurality of dimensions; obtaining a homogeneous resource graph corresponding to each resource, the graph including resource feature nodes of the corresponding resource in a plurality of dimensions; and training a prediction network based on the heterogeneous conversion graph, the homogeneous object graph of each object, and the homogeneous resource graph of each resource, to obtain a trained prediction network configured to predict a conversion index of an object of interest for a resource of interest.