Data Subscription Management with Resource Auction
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Solution Overview
Problem
Existing methods for data analysis, such as centralized search engines, are not scalable for cross-referencing queries and are inefficient in managing user subscriptions to large-scale data resources due to cost and resource constraints, especially when dealing with proprietary and privately held data sources.
Innovation Solution
A system comprising a data store, communications interface, resource allocation manager, and user agents that select and manage data subscriptions, allowing for efficient data transfer and analysis, with a resource auction process to prioritize and allocate system resources based on user preferences and data utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If centralized search engines index all information to enable comprehensive queries, then query capability is improved, but system cost and scalability are worsened
Solution Approach 1:
The patent extracts only the necessary data from large-scale internet stores and communities into a local data processing unit, rather than indexing all information centrally. This selective extraction enables comprehensive query capability while avoiding the prohibitive cost of storing and processing all available data.
Solution Approach 2:
The system segments data management by maintaining local copies of relevant data in a local data processing unit while retaining access to remote data sources. This segmentation allows the system to provide sophisticated query capability without requiring a centralized infrastructure to handle all data.
2Adaptability or versatility
If all data is stored and indexed in a massive centralized index, then search capability is improved, but data processing efficiency and scalability are worsened
Solution Approach 1:
The system extracts only the data needed for specific queries from remote sources and processes it locally, rather than maintaining a massive centralized index. This extraction approach improves data processing efficiency by working with smaller, relevant data sets while preserving comprehensive search capability.
Solution Approach 2:
The local data processing unit acts as an intermediary between users and remote data sources. It maintains local copies of relevant data for efficient processing while having the capability to query remote sources when needed, thus improving overall data processing efficiency without sacrificing search capability.
3Adaptability or versatility
If proprietary and private data is loaded into centralized infrastructure for analysis, then analysis capability is improved, but data security and compliance are worsened
Solution Approach 1:
The system extracts only the specific data needed for analysis from remote sources and processes it locally in the data processing unit, rather than loading all proprietary and private data into a centralized infrastructure. This approach enables analysis capability while minimizing data security risks by keeping sensitive data localized and reducing its exposure to centralized systems.
Solution Approach 2:
The system implements local data processing and analysis capabilities within the data processing unit, allowing proprietary and private data to be analyzed locally without being transferred to centralized infrastructure. This local quality approach preserves analysis capability while enhancing data security and compliance.
4Quantity of substance
If users subscribe to multiple data sources, then information completeness is improved, but resource management complexity is worsened
Solution Approach 1:
The system enables users to subscribe to multiple data sources and automatically manages the data collection and processing resources. The resource allocation manager automatically selects which subscriptions to process and allocates system resources accordingly, reducing the manual resource management complexity while maintaining information completeness.
Solution Approach 2:
The system incorporates feedback mechanisms where the resource allocation manager monitors and adjusts resource allocation based on user subscriptions and data processing needs. This feedback loop enables the system to manage multiple data sources efficiently, maintaining information completeness while adapting to changing resource requirements.
Data Source
AI summary
The present invention, provides a method of data analysis in which data subscriptions are defined and data for that subscription be collected for analytical purposes. Supplemental queries based on new information received can be generated automatically and old queries can be eliminated automatically on the basis that they are rendered obsolete in. terms of not providing novel information in comparison to other queries and their results not being used.