Viewing Condition Probability Calculator for Multi-Viewer Households
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Determining the viewing conditions for media events in households with multiple individuals is challenging due to the complexity of calculating probabilities for various viewer combinations, especially when specific individuals or groups are watching specific media devices.
Innovation Solution
A method and apparatus that utilize independent viewing probabilities for each household member to enumerate and calculate the probabilities of different viewing conditions by considering combinations of viewers, allowing for the determination of unconditional and normalized probabilities for various viewing scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional audience measurement methods are used to collect viewing habits, then demographic data can be gathered, but determining specific viewing conditions in households with multiple individuals becomes complex and inaccurate
Solution Approach 1:
The patent segments the household population into discrete individuals, each with their own independent viewing probability. By treating each person as a separate entity with binary states (viewing or not viewing), the complex problem of determining group viewing conditions is broken down into manageable individual probability calculations that can be systematically combined.
Solution Approach 2:
The patent performs preliminary enumeration of all possible viewing combinations before calculating probabilities. By pre-defining the sample space of all possible viewing scenarios (e.g., person A watching, person B not watching, etc.), the system establishes a structured framework that simplifies subsequent probability calculations and avoids complex real-time computations.
2Reliability
If independent viewing probabilities are calculated for each household member, then comprehensive viewing condition probabilities can be determined, but the computational process becomes increasingly complex with more people
Solution Approach 1:
The patent divides the household into independent individual units, each contributing their own viewing probability. This segmentation allows the use of basic probability multiplication rules for independent events, transforming a complex group behavior problem into a series of simple individual probability calculations that scale linearly rather than exponentially.
Solution Approach 2:
The patent merges individual viewing probabilities through systematic combination rules to derive group viewing condition probabilities. By combining individual binary states (viewing/not viewing) according to probability theory, the system aggregates individual data into comprehensive household-level viewing condition probabilities without requiring complex interaction models.
3Measurement precision
If all possible viewing combinations are enumerated to determine probabilities, then accurate viewing condition data is obtained, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary enumeration and organization of all possible viewing combinations before probability calculation. By pre-structuring the sample space and categorizing combinations according to viewing conditions of interest, the system reduces redundant calculations and enables efficient probability derivation from the organized combinatorial framework.
Solution Approach 2:
The patent segments the enumeration process into manageable components, organizing combinations by specific viewing conditions (e.g., number of viewers, specific individuals watching). This structured segmentation allows selective calculation of probabilities for conditions of interest rather than computing all possible scenarios, reducing computational overhead while maintaining accuracy.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed for a viewing condition probability calculator. The viewing condition probability calculator enumerates a list of all viewing combinations for a tuning event, for a number of people N at a location. A probability for each of the viewing combinations is determined, using an independent probability of viewing for each of the N people at the location. A probability of a viewing condition is determined using the probabilities of a first set of viewing combinations that have a first common characteristic.