Information Pushing System Target User Selection
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Solution Overview
Problem
Current information push methods require manual selection of target users, leading to operational complexity and decreased information clicking ratios due to subjective and imprecise targeting.
Innovation Solution
A method and apparatus that automatically select target users based on collected pushing parameters, including time of information push, user interaction data, and information visiting trends, to calculate and prioritize users with higher information clicking ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of target users is used, then operational simplicity is maintained, but information clicking ratio decreases due to subjective and imprecise targeting
Solution Approach 1:
The system automatically selects target users based on their own historical behavior data (visiting records, clicking habits, information preferences) without requiring manual intervention. The user database self-updates with interaction data, and the selection algorithm autonomously identifies high-probability target users, making the system self-servicing and eliminating manual operational complexity
Solution Approach 2:
The patent replaces the mechanical manual selection process with an automated computational system that uses algorithms to analyze user behavior data and calculate clicking probabilities. This substitution of mechanical human judgment with automated data processing achieves precise targeting while eliminating operational complexity
2Productivity
If automated selection based on multiple parameters is implemented, then information clicking ratio increases, but system complexity increases
Solution Approach 1:
The system pre-collects and stores user behavior data (visiting records, clicking habits, information preferences) in the user database before the information push operation. By preparing this data in advance, the actual selection process only requires retrieving and analyzing pre-processed information, which simplifies the real-time system complexity while maintaining high clicking ratio through comprehensive parameter analysis
Solution Approach 2:
The patent introduces a user database as an intermediary layer between the information push system and the user selection process. This database stores and organizes user behavior data, serving as a mediator that provides structured input to the selection algorithm. The intermediary database simplifies system complexity by centralizing data management and providing ready-to-analyze user profiles
Data Source
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AI summary
The present application provides an information pushing method and apparatus. The method comprises: collecting a pushing parameter of each piece of information pushed in a time segment T, the pushing parameter comprising information pushing time, an information pushing user, or the number of times of the information being accessed; determining, according to the collected pushing parameter, an information access parameter of each user in the time segment T, the information access parameter comprises at least: the number of times of the information being visited in the time segment T, an information access tendency, and time of a last access of the information in T, and the information access tendency being determined by the number of times of the information being accessed; and selecting, according to the information access parameter of each user in the time segment T, a target user meeting a requirement, and pushing information to the target user.