Location-Tagged Media Recommendations From Consumption Patterns
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Solution Overview
Problem
Existing media recommendation systems fail to account for the geographic location where media assets are consumed, instead relying only on the location of creation, leading to inefficient content distribution and user recommendations.
Innovation Solution
A media guidance application that tags media assets with locations of frequent consumption, monitors user viewing history, and recommends media based on these locations, using a database to store and retrieve geographic locations associated with media asset consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If media recommendation systems use only the location where a user created the media asset, then the system is simple to implement, but the recommendation accuracy and relevance to user consumption patterns deteriorates
Solution Approach 1:
The system pre-tags media assets with geographic location information based on consumption data before recommendations are generated. This preliminary tagging action allows the system to quickly retrieve location-relevant content without complex real-time analysis, improving recommendation accuracy while maintaining implementation simplicity
Solution Approach 2:
The patent introduces geographic location tags as an intermediary element between user consumption behavior and recommendation generation. These tags serve as a mediator that connects consumption patterns to relevant content recommendations, enhancing accuracy without requiring complex direct analysis of consumption data
2Adaptability or versatility
If the system monitors and tags media assets based on consumption locations of multiple users, then recommendation relevance improves, but system complexity and data processing requirements increase
Solution Approach 1:
The system extracts only the essential geographic location information from complex consumption data, separating this key feature from other detailed consumption patterns. This extraction approach maintains recommendation relevance by focusing on location while reducing system complexity by ignoring less critical data dimensions
Solution Approach 2:
The patent transforms consumption location data into standardized geographic tags with specific parameters (latitude, longitude, location name). This parameter standardization allows the system to handle diverse consumption data uniformly, improving adaptability while managing complexity through consistent data structures
3Manufacturing precision
If the system stores detailed consumption location data for all users, then content distribution accuracy improves, but data storage requirements and processing time increase
Solution Approach 1:
The system performs preliminary aggregation of consumption location data into location-based popularity metrics before distribution decisions are made. This pre-processing action stores summarized location statistics that enable quick retrieval and accurate content distribution without requiring real-time analysis of individual consumption records
Solution Approach 2:
The patent implements partial data retention by storing only the most significant consumption location information (frequently consumed locations) rather than all consumption data. This selective storage approach maintains distribution accuracy for relevant content while reducing overall data volume and processing requirements
Data Source
AI summary
Methods and systems are provided herein for recommending a media asset based on a geographic location at which that media asset was frequently consumed. For example, the system may monitor a location, such as New York City or Times Square, to determine popular media assets watched there, such as “The Avengers,” and when another user visits New York City, the system may then notify the user that the movie, such as “The Avengers,” is associated with New York City. The system stores the geographic locations associated with the media asset in the database based on the consumption of the media asset so that other users may be notified which media assets are associated with each geographic location.