Personalized Details Page Layout Using Reading Behavior Feedback

The patent implements dynamic subject area arrangement by collecting user reading behavior data (reading duration, scrolling behavior, clicking) and automatically adjusting the order and visibility of subject areas based on user preferences. The system transitions from static preset ordering to dynamic personalized ordering, where subject areas are reordered based on user interaction patterns without requiring manual user configuration.

The system establishes a feedback loop by continuously collecting user reading data (reading duration for each subject area, scrolling depth, clicking behavior) and using this feedback to adjust the subject area arrangement on subsequent detail pages. The server analyzes user behavior patterns and automatically optimizes the display order, creating a closed-loop system that improves user experience through data-driven adjustments.

The patent extracts and removes subject areas that users demonstrate low interest in, based on collected reading behavior data. When user data indicates certain subject areas are consistently skipped, read for minimal duration, or scrolled past quickly, the system automatically excludes these subject areas from the detail page display, presenting only the subject areas that match user preferences while maintaining completeness of relevant information.

The system applies different display qualities to different subject areas based on user preferences. High-preference subject areas are displayed with full content and prominent positioning, while low-preference subject areas are either excluded entirely or displayed with reduced visibility. This local differentiation optimizes the overall page quality by ensuring each subject area receives appropriate attention based on user interest.

The system implements self-service personalization by automatically collecting user reading data, analyzing behavior patterns, and adjusting subject area arrangements without requiring manual user input or configuration. The system serves itself by using its own collected data to optimize the user experience, eliminating the need for complex user profile management interfaces or manual preference settings.

The system performs preliminary data collection and analysis by gathering user reading behavior data in advance and pre-processing it to identify user preferences. The server maintains pre-computed user preference profiles that can be quickly applied when generating personalized detail pages, reducing real-time processing requirements and enabling fast personalization delivery.