DVR Watched Log Database for Recording Conflict Resolution
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Solution Overview
Problem
Current digital video recorder (DVR) devices lack an effective system to track user viewing patterns and preferences, leading to unnecessary recording of shows and limited storage capacity, as users often delete recorded episodes due to lack of personalized recording decisions.
Innovation Solution
A method and system that collect and store DVR viewer metrics in a 'Watched Log' database, using viewing information to determine future recording decisions, incorporating a rules engine for conflict management and user preference integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If DVR devices record multiple television shows to maximize storage utilization, then the quantity of recorded content increases, but users frequently delete already-viewed episodes due to lack of personalized recording decisions
Solution Approach 1:
The system automatically tracks user viewing patterns and makes recording decisions without requiring manual user intervention. The DVR monitors which shows users watch, how often they watch them, and uses this data to automatically determine future recording decisions, eliminating the need for users to manually manage their recording libraries
Solution Approach 2:
The system implements a feedback loop where user viewing behavior is continuously monitored and fed back into the recording decision-making process. The Watched Log database stores viewing metrics that inform future recording decisions, creating a closed-loop system that adapts to user preferences over time
2Adaptability or versatility
If DVR devices use broad category-based recording to expand content variety, then the diversity of recorded shows increases, but the device continually records shows that users do not want to watch
Solution Approach 1:
The system transitions from uniform category-based recording to personalized, show-specific recording decisions. By analyzing individual user viewing patterns for each show, the system tailors recording decisions to local user preferences rather than applying blanket category rules, ensuring that recording decisions reflect actual user interests
Solution Approach 2:
The recording system dynamically adapts to changing user preferences over time. Rather than using static category definitions, the system continuously updates its understanding of user preferences based on evolving viewing patterns, allowing recording decisions to remain aligned with user interests as they change
3Quantity of substance
If DVR devices limit hard drive space allocation, then storage capacity is optimized, but the number of recordable television shows is restricted
Solution Approach 1:
The system dynamically adjusts recording parameters such as recording quality, resolution, and compression settings based on user viewing patterns and storage availability. By changing these parameters adaptively, the system maximizes the number of shows that can be stored within the fixed hard drive capacity while maintaining acceptable quality for user preferences
Data Source
AI summary
A method and system are provided in which DVR viewer metrics are collected and saved in a “Watched Log” data base including identifying titles and other features of recorded DVR programs. User viewing metrics are collected and saved for use in determining whether or not future shows are recorded. After a DVR user watches a TV or other video show episode, the show episode will be added to the Watched Log. Subsequently, before recording a new TV show, the DVR device can determine the viewer's actions with regard to previous similar shows and factor such information into a decision regarding the recording of the new show.