Intelligent Recording via Viewing Pattern Analysis
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Solution Overview
Problem
Users often miss potentially interesting shows due to cumbersome navigation through numerous channels and shows in content receivers, despite existing recording technologies not effectively addressing this issue.
Innovation Solution
An intelligent recording method that tracks users' viewing habits and interactions to identify and automatically record scheduled program content based on their viewing patterns, using a content receiver with modules for data collection, learning, and recording.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually navigate through EPG to find and record shows, then recording functionality is available, but the navigation process becomes cumbersome and time-consuming
Solution Approach 1:
The system automatically performs the recording function by monitoring user viewing habits and autonomously identifying shows to record, eliminating the need for manual navigation and timer setup by the user
Solution Approach 2:
The system collects feedback on user viewing patterns and interactions with the content receiver, then uses this feedback to automatically determine which shows to record, creating a closed-loop system that adapts to user preferences
2Reliability
If automatic recording based on viewing patterns is implemented, then users do not miss favorite shows, but the system complexity increases
Solution Approach 1:
The content receiver performs multiple functions including traditional recording, viewing habit monitoring, data aggregation, pattern analysis, and automatic program identification within a single integrated system
Solution Approach 2:
The system introduces an intermediary processing layer that collects viewing data, aggregates it, and analyzes patterns to bridge the gap between user behavior and automatic recording decisions
Data Source
AI summary
An intelligent recording collects data associated with a user's viewing habit of live program contents and determines a viewing pattern by analyzing the collected data. The viewing pattern is used to identify a scheduled program content as a candidate for automatic recording, the identified scheduled program content having fallen within the determined viewing pattern.