Automatic Recording Timer Based on Web Activity Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face inconvenience in setting timers to record program content as they need to navigate through program guides, and there is no efficient way to automatically suggest or set timers based on user web activity data.
Innovation Solution
A system that collects user web activity data from search history, browsing, and social media, compares it with program content metadata, and automatically sets timers on receiving devices like set-top boxes or DVRs to record relevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually navigate program guides to set timers, then recording accuracy is improved, but user convenience deteriorates
Solution Approach 1:
The system automatically monitors user web activity and autonomously sets recording timers without requiring manual user intervention. The receiving device compares collected web activity data with program content metadata to automatically determine what to record, eliminating the need for users to navigate program guides while maintaining accurate recording based on actual user interests.
Solution Approach 2:
The system performs preliminary analysis of user web activity data before the actual recording decision is needed. By continuously monitoring and analyzing user browsing history, search queries, and social media activity in advance, the system prepares recommendation data that enables automatic timer setting without requiring last-minute manual navigation.
2Ease of operation
If automatic timer setting based on web activity is implemented, then user convenience is improved, but system complexity increases
Solution Approach 1:
The system introduces a recommendation engine as an intermediary component that bridges web activity data and recording decisions. This intermediary analyzes user behavior patterns and translates them into recording recommendations, managing the complexity of correlating diverse web activity types with appropriate program content without requiring direct complex integration between all system components.
Solution Approach 2:
The system segments the complex task of automatic timer setting into distinct functional modules: web activity data collection, data processing and analysis, program content metadata comparison, and timer setting execution. This modular segmentation allows each component to handle specific aspects of the complexity independently, making the overall system more manageable and maintainable.
3Measurement precision
If web activity data collection is expanded, then recommendation accuracy is improved, but data privacy concerns increase
Solution Approach 1:
The system extracts only the specific web activity data elements that are directly relevant to program content recommendations, such as browsing history related to entertainment topics, search queries about shows or movies, and social media activity related to content consumption. By selectively extracting only necessary data points rather than collecting all web activity data, the system improves recommendation accuracy while minimizing privacy intrusion.
Data Source
AI summary
Systems and methods for automatically recording content based on user web activity data are provided. One such method includes receiving, by a receiving device, user web activity information associated with a user of the receiving device. The receiving device further receives content information associated with program content that will be available for viewing via the receiving device at a future time. The received user web activity information and the content information are compared to determine program content relevant to the user. A timer is automatically set, in advance of a time when the relevant program content will be available for viewing, to record the program content relevant to the user when the program content becomes available for viewing.