Merging Multiple Data Sets for Accurate TV Guide Information
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Solution Overview
Problem
The process of collecting and merging information about television shows from multiple sources, such as IMDB, All Movie Guide, and Tribune Media Services, is inefficient due to inaccuracies and the need for significant human involvement, resulting in incomplete and inaccurate data.
Innovation Solution
A system that merges data from multiple sources by matching references to the same person across different sources, selecting the most reliable biographical information, and generating a combined data set that is more complete and accurate, using a computer system to collect, normalize, and compare data sets, and assign unique identifiers for accurate association of relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If information is collected from multiple sources to improve completeness, then the quantity of information increases, but inaccuracies and data quality issues worsen
Solution Approach 1:
The patent merges multiple source data sets by collecting information from multiple sources (IMDB, AMG, TMS) and combining them into a unified data structure. This allows the system to accumulate information from diverse sources while maintaining the ability to evaluate and select the most reliable data through comparison and validation processes.
Solution Approach 2:
The system implements feedback mechanisms by comparing data across multiple sources, identifying inconsistencies, and using this information to improve data quality. The merging process includes validation steps that feed back into the data collection and selection process, allowing the system to learn from and correct inaccuracies.
2Reliability
If manual review processes are used to improve data accuracy, then reliability increases, but the time and resources required increase significantly
Solution Approach 1:
The system performs self-service by automatically collecting, comparing, and validating data from multiple sources without requiring extensive manual intervention. The automated merging process includes built-in validation and conflict resolution mechanisms that operate independently, significantly reducing the time and human resources needed while maintaining data accuracy.
Solution Approach 2:
The patent replaces manual mechanical review processes with automated computer-based systems. The system uses algorithmic comparison, data validation, and automated conflict resolution to substitute human reviewers, dramatically reducing the time required for data verification while maintaining or improving accuracy through systematic processing.
3Quantity of substance
If data from multiple sources is merged to improve completeness, then the quantity of information increases, but the complexity of the merging process increases
Solution Approach 1:
The merging process is segmented into distinct modular steps: data collection from individual sources, data normalization and standardization, comparison and validation, conflict resolution, and final merging. This segmentation allows each step to be handled independently with specific processing rules, reducing overall complexity while achieving complete information integration.
Solution Approach 2:
The system implements a universal merging framework that can handle multiple data sources with different formats and structures through a single standardized process. The normalization and validation mechanisms are designed to work across diverse sources (IMDB, AMG, TMS), providing a multi-functional solution that reduces complexity by avoiding source-specific processing logic.
4Reliability
If human involvement is increased to ensure information accuracy, then reliability improves, but productivity decreases
Solution Approach 1:
The system achieves self-service by implementing automated data validation, comparison, and verification processes that previously required human reviewers. The automated system continuously monitors and validates data from multiple sources, maintaining high accuracy levels while dramatically improving productivity through parallel processing and elimination of manual review bottlenecks.
Data Source
AI summary
A method may comprise comparing a first data set with a second data set, the first data set associating a first plurality of names with a first plurality of roles, and the second data set associating a second plurality of names with a second plurality of roles. The method may further comprise generating a third data set based on an outcome of the comparing, such that the third data set associates a subset of the first plurality of names with a subset of the second plurality of roles. Apparatuses, methods, and software for performing these and other functions are also described.