Data Item Recommendation via Application Type Criteria
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Solution Overview
Problem
Traditional data protection systems only perform file name matching searches across multiple storage devices, failing to provide optimal data item recommendations for users, especially in scenarios requiring disaster recovery or cost-effective data access.
Innovation Solution
A method that receives a data item request from a terminal device including an identifier and application type, determining a recommendation criterion type based on the application type to recommend suitable data items from multiple storage devices, optimizing recommendations for performance or cost sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional file name matching search is performed among multiple storage devices, then the search coverage is comprehensive, but the recommendation accuracy is insufficient
Solution Approach 1:
The patent changes the search parameters from simple file name matching to multi-dimensional parameters including application type, data item type, storage device location, and access cost. This allows the system to provide customized recommendations based on different application scenarios such as disaster recovery, data analysis, or casual access, thereby improving recommendation accuracy while maintaining comprehensive search coverage across multiple storage devices
2Reliability
If data items are stored in multiple storage devices for data protection, then the data reliability is improved, but the access cost increases
Solution Approach 1:
The patent implements a feedback mechanism where the system evaluates multiple factors including data item type, application type, storage device location, and access cost to determine the optimal data copy for retrieval. The system provides feedback to users about the recommended data item and its associated access cost, allowing users to make informed decisions about data recovery operations and potentially reduce unnecessary access costs while maintaining data protection
3Measurement precision
If comprehensive data item information is collected for recommendation, then the recommendation relevance is improved, but the system complexity increases
Solution Approach 1:
The patent segments the recommendation system into distinct functional modules: a data collection module that gathers information about data items and storage devices, a data processing module that analyzes the collected information according to different application types, and a recommendation generation module that produces customized recommendations. This segmentation allows the system to handle comprehensive information effectively while managing complexity through modular design, where each module has a specific responsibility
Data Source
AI summary
Embodiments of the present disclosure relate to a method, an electronic device, and a computer storage medium for data item recommendation, and relate to the field of information processing. According to this method, a request for a data item is received from a terminal device, the request includes an identifier for identifying the data item and an application type; the application type indicates a type of use of the data item; a recommendation criterion type matching the request is determined based on the application type, the recommendation criterion type indicates a type of a criterion based on which the data item is recommended, a plurality of data items associated with the identifier are determined the plurality of data items are located in a plurality of storage devices and based on the recommendation criterion type, a recommended data item is determined from the plurality of data items as a response.