EPG affinity clusters for content recommendation
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Solution Overview
Problem
Viewers face difficulty in finding relevant content amidst the vast amount of available movies, music, and television programs due to the sheer quantity of choices, leading to time wastage in searching for interesting content.
Innovation Solution
Electronic program guide (EPG) affinity clusters are formed based on the assumption that programs scheduled in corresponding timeslots are targeted to the same or similar audiences, using metadata such as titles, cast, and crew information to establish relationships and provide recommendations for viewing, recording, or setting reminders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the quantity of content choices is increased, then the variety of programs available to viewers is improved, but the time required for viewers to search for relevant content increases
Solution Approach 1:
The patent segments the vast content library into affinity clusters based on metadata relationships (cast, crew, genres). This organization divides the content into manageable, thematically related groups that can be efficiently browsed and searched through, reducing the time needed to find relevant content while maintaining variety.
Solution Approach 2:
The patent introduces an intermediary search and recommendation system that uses affinity clusters as a mediator between the viewer and the content library. This intermediary structure organizes content based on metadata relationships, enabling faster discovery of relevant programs without requiring viewers to manually search through all available content.
2Measurement precision
If metadata collection and affinity cluster formation are performed, then the accuracy of program recommendations is improved, but the system complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-processing and storing metadata (cast, crew, genres) and forming affinity clusters in advance. This preparation enables accurate recommendations to be generated quickly during user interaction without requiring complex real-time analysis, thus improving recommendation accuracy while managing system complexity through proactive data organization.
Data Source
AI summary
Techniques are described in which electronic program guide (EPG) affinity clusters may be formed based upon an assumption that programs scheduled in corresponding timeslots are targeted to the same or similar audiences. In at least some embodiments, data for an EPG is examined to identify programs that are scheduled in timeslots designated as corresponding. Metadata related to the identified programs is collected. The metadata may include titles as well as cast/crew data related to the programs. One or more affinity clusters may be formed using the collected metadata to establish relationships between actors, directors, titles and other items of the metadata. The affinity clusters may be used to provide recommendations including recommendation to view, record, or set a reminder for programs according to the relationships established by the affinity clusters.