Electronic Book Pushing System Using Reading Duration Analysis
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Solution Overview
Problem
Existing methods for pushing electronic books fail to consider user reading habits and preferences, leading to a mismatch between pushed content and user expectations, resulting in low relevance and effectiveness.
Innovation Solution
A method and apparatus that acquire reading duration information from terminals to determine user reading preferences and average reading durations, allowing for targeted electronic book recommendations based on these metrics, ensuring the pushed content aligns with user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If electronic book recommendations are made based on read contents only, then the pushing system is simple to implement, but the relevance and accuracy of recommendations deteriorates
Solution Approach 1:
The patent segments user reading behavior into multiple independent dimensions: read contents, reading duration, and reading habits. Each dimension is analyzed separately to extract specific features (e.g., reading speed, pause frequency, completion rate), which are then combined to form a comprehensive user profile for more accurate recommendations without overwhelming system complexity
Solution Approach 2:
The patent adds new dimensions to the recommendation system by incorporating temporal data (reading duration) and behavioral patterns (reading habits) alongside content-based features. This multi-dimensional approach transforms the recommendation from a single-factor system to a multi-factor system, significantly improving recommendation accuracy while maintaining manageable complexity through modular processing
2Measurement precision
If reading duration information is collected and analyzed from multiple terminals, then recommendation relevance improves, but network traffic and data processing load increase
Solution Approach 1:
The patent extracts only the essential and most informative features from the collected reading duration data, such as average reading speed, total reading time, and completion rates. By filtering out redundant information and focusing on key metrics, the system achieves high recommendation relevance while minimizing the amount of data that needs to be transmitted and processed
Solution Approach 2:
The patent implements a selective data collection strategy where reading duration information is collected and analyzed only when it provides meaningful insights for recommendations. Not all reading data is processed equally - the system focuses on significant reading sessions and patterns, avoiding unnecessary data transmission and processing while maintaining recommendation quality
Data Source
AI summary
A method and device for pushing an electronic book. the method comprises: obtaining reading duration information sent by multiple terminals (210), the reading duration information comprising identity information of the terminals, identifier information of electronic books read by users of the terminals, and reading time information corresponding to the identifier information; determining, according to the reading time information, reading preference information of the terminals corresponding to the identity information and average reading durations of the electronic books corresponding to the identifier information (220); and pushing a first electronic book to a first terminal according to the reading preference information and the average reading durations (230), the average reading duration of the first electronic book matching the reading preference information of the first terminal. By means of the method and the device, targeted pushing of electronic books is implemented.