Video Distribution Recommendation via Multi-Source Metadata Analysis
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Solution Overview
Problem
Conventional methods for identifying opportunities to increase data distribution are limited as they primarily focus on analyzing data attributes and fail to consider other potentially relevant types of data, thereby missing additional distribution opportunities.
Innovation Solution
A computer-implemented method that receives metadata of a video, retrieves additional metadata from a video sharing network and a second network, generates profiles for the video and distribution channels, and analyzes these profiles to identify adjacent channels with common characteristics, providing recommendations for increased distribution by distributing the video in these channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional methods focus only on analyzing data attributes, then the analysis process remains simple, but distribution opportunities are missed
Solution Approach 1:
The patent transitions from analyzing only data attributes (one dimension) to analyzing multiple data types including attributes, metadata, and contextual information (multiple dimensions). This dimensional expansion enables comprehensive distribution opportunity identification by examining videos, channels, users, and external data sources simultaneously, resolving the contradiction between analysis depth and system complexity.
Solution Approach 2:
The system implements multi-functionality by integrating diverse data sources (video attributes, metadata, channel information, user data, external networks) into a unified analysis platform. This universal approach allows the system to perform multiple analysis functions concurrently, identifying distribution opportunities across different dimensions without requiring separate specialized systems.
2Productivity
If only video attributes are analyzed, then the analysis process is fast, but distribution opportunities are limited
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching metadata from video sharing networks and external data sources before actual distribution opportunity analysis is needed. This advance preparation reduces processing time during critical analysis phases, enabling comprehensive multi-source analysis without significant time loss, thus resolving the contradiction between analysis completeness and processing speed.
Solution Approach 2:
The system implements self-service mechanisms where the analysis platform automatically retrieves and processes data from multiple sources without requiring manual intervention for each data type. This automated self-service approach handles the complexity of multi-source data integration efficiently, expanding distribution reach while minimizing additional time investment from users.
3Measurement precision
If comprehensive data from multiple sources is collected, then distribution opportunities are better identified, but system complexity increases
Solution Approach 1:
The patent introduces intermediary components that act as mediators between diverse data sources and the core analysis system. These intermediaries standardize data formats, filter relevant information, and manage data flows from video sharing networks, external networks, and internal sources. This intermediary layer enables precise distribution opportunity identification while managing system complexity through standardized interfaces and automated data processing.
Data Source
AI summary
A computer-implemented method includes receiving, by a first computing device, an identification of a video and an identification of a distribution channel of the video. The method includes retrieving, by the first computing device, from a video sharing network, metadata associated with a video. The method includes retrieving, by the first computing device, from a second computing device in a second network, data having at least one characteristic in common with the metadata. The method includes generating, by the first computing device, a profile of the video based on the retrieved data and the metadata. The method includes generating, by the first computing device, a profile of the distribution channel based on the retrieved data and metadata. The first computing device generates a recommendation for a method to increase a level of distribution of the video. The first computing device provides, to a user, the recommendation.