Personalized Network Information Push via Browser Data Classification
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Solution Overview
Problem
Users face difficulty in obtaining relevant network information due to the lack of consideration for their intentions when network information is pushed, as existing methods broadcast the same information to all users without accounting for individual preferences or behaviors.
Innovation Solution
A method and apparatus that utilize a server to obtain, classify, and push network information based on user browser data, employing a classification model to determine user intentions and provide relevant information by categorizing and matching browser data with appropriate network content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network information is pushed via navigation page to all users, then network information can be delivered to users, but user intention is not considered and information relevance deteriorates
Solution Approach 1:
The patent applies local quality by transitioning from uniform information delivery to personalized information pushing. The server analyzes individual user browser data and pushes network information tailored to each user's specific interests and behavior patterns, making the information delivery adaptive to local user characteristics rather than applying a one-size-fits-all approach.
Solution Approach 2:
The patent implements parameter changes by using classification models to transform raw browser data into categorized user profiles. The system dynamically adjusts information pushing parameters based on user behavior analysis, changing the delivery parameters according to user intentions and preferences to optimize information relevance.
2Measurement precision
If classification model is used to analyze browser data, then user intention can be identified, but system complexity increases
Solution Approach 1:
The patent applies self-service by enabling the system to automatically analyze and classify user browser data without manual intervention. The classification model autonomously processes user behavior data, identifies patterns, and determines user intentions, making the complex analysis process self-executing and reducing the need for manual system configuration.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors user browser data and adjusts information pushing strategies based on classified user intentions. The classification results feed back into the information selection and delivery process, creating a closed-loop system that refines its accuracy over time while managing complexity through iterative learning.
Data Source
AI summary
A method and apparatus for pushing network information are provided. The method includes: obtaining browser data uploaded by a browser; classifying the browser data uploaded via a classification model and determining a category of the browser data; obtaining network information related to the category, pushing the network information obtained to the browser.