Sound Recording-Composition Link Inference With Owner Approval
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Solution Overview
Problem
Conventional content sharing platforms face inaccuracies and inefficiencies in managing complex ownership structures due to incorrect or missing connections between sound recordings and compositions, leading to laborious manual corrections and inefficient use of computing resources.
Innovation Solution
A rights management component with a connection proposal generator infers and proposes potential connections between sound recordings and compositions based on existing data, allowing owners to accept or reject these connections, thereby enhancing the accuracy and completeness of ownership data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to establish connections between sound recordings and compositions, then accuracy of connections can be maintained through human verification, but labor efficiency deteriorates due to laborious manual corrections
Solution Approach 1:
The system performs self-service by automatically generating hypothesis connections between sound recordings and compositions using inference algorithms. The server device autonomously creates hypothesized connections based on available data without requiring manual intervention for each connection, thereby improving productivity while maintaining accuracy through subsequent verification mechanisms.
Solution Approach 2:
The hypothesis data structure serves as an intermediary between the serving data structure and final accurate connections. It introduces hypothesized connections that bridge the gap between existing explicit connections and missing implicit connections, allowing the system to efficiently propose connections that can then be verified and accepted, resolving the contradiction between automated efficiency and accuracy.
2Productivity
If automated inference methods are used to generate connections between sound recordings and compositions, then productivity improves through reduced manual intervention, but measurement precision deteriorates due to potential inaccuracies in inferred connections
Solution Approach 1:
The system performs preliminary action by generating hypothesis connections in advance before final verification. The server device creates hypothesized connections based on inferred data, which are then presented for approval. This preliminary generation of connections improves productivity by automating the initial connection creation process while maintaining precision through the subsequent approval mechanism.
Solution Approach 2:
The system implements feedback by requiring approval of hypothesized connections before they are added to the serving data structure. The approval mechanism provides feedback on the accuracy of inferred connections, allowing the system to learn and improve. This feedback loop ensures that while automated inference improves productivity, accuracy is maintained through verification and correction of incorrect inferences.
3Reliability
If complete manual verification of all connections is performed, then reliability of ownership data improves, but loss of time increases due to extensive manual review required
Solution Approach 1:
The system applies partial action by requiring verification only for hypothesized connections rather than all connections. Existing explicit connections in the serving data structure remain unchanged and do not require re-verification. This partial verification approach maintains reliability for connections that need verification while reducing time loss by avoiding redundant verification of already validated connections.
4Loss of information
If the serving data structure is frequently updated with new connections, then completeness of ownership information improves, but device complexity increases due to management of hypothesis and serving structures
Solution Approach 1:
The system segments the connection management process into two distinct data structures: the serving data structure containing verified explicit connections, and the hypothesis data structure containing inferred connections pending approval. This segmentation allows the system to maintain completeness by exploring hypothesized connections while managing complexity through clear separation of verified and unverified data, with distinct management procedures for each structure.
Data Source
AI summary
Implementations disclose determining connections between sound recordings and compositions. A method includes maintaining, by a server device of a content sharing platform, a serving structure to represent resources comprising sound recording resources and composition resources and explicit connections between the resources, identifying inferred connections between the resources based on data comprised in the resources of the serving structure, and upon receiving a user approval of at least one of the inferred connections, adding, by the server device, the at least one of the inferred connections to the serving structure.