Data Processing Device Feature-Based Compression Parameter Prediction
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Solution Overview
Problem
The challenge lies in selecting an appropriate compression format and parameters for data processing, as the compression effect varies significantly with data content, making it difficult to predict outcomes until the process is executed, leading to inefficient storage and real-time processing issues.
Innovation Solution
An information processing device and method that extract feature amounts from data, match them with reference feature amounts in a database, and predict processing results, allowing for the selection of optimal formats and parameters before processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If data is compressed using various compression formats or parameters in advance, then compression effectiveness can be improved, but massive storage capacity is occupied by preliminarily compressed data
Solution Approach 1:
The system performs preliminary analysis of data features and predicts optimal compression parameters before actual compression occurs. By extracting feature amounts from the original data and matching them with reference feature amounts in a database, the system determines the best compression format and parameters in advance, avoiding the need to store multiple pre-compressed versions of the data.
Solution Approach 2:
Instead of storing multiple actual compressed data versions, the system creates a virtual copy of the compression results by storing only the predicted optimal parameters and feature amounts in a database. This allows the system to retrieve and apply the appropriate compression settings without occupying massive storage space with redundant compressed data files.
2Manufacturing precision
If data is compressed using various compression formats or parameters in advance, then compression effectiveness can be improved, but it becomes difficult to appropriately process data requiring real-time provision
Solution Approach 1:
The system performs preliminary analysis of data features and predicts optimal compression parameters before actual compression occurs. By extracting feature amounts from the original data and matching them with reference feature amounts in a database, the system determines the best compression format and parameters in advance, avoiding the need to store multiple pre-compressed versions of the data.
Solution Approach 2:
The system enables real-time processing by making the compression decision process self-sufficient and automated. The feature amount extraction unit, matching unit, and parameter determination unit work together to automatically select optimal compression parameters without manual intervention or pre-computation of multiple versions, allowing rapid processing of data requiring real-time provision.
3Ease of operation
If the same compression format and parameter setting are used, then processing simplicity is maintained, but compression effect varies significantly according to content of the data
Solution Approach 1:
The system applies different compression parameters to different data based on their specific characteristics. By extracting feature amounts that represent the content characteristics of each data file and matching them with reference features in a database, the system determines locally optimized compression parameters for each data type, ensuring high compression effectiveness while maintaining processing simplicity through automation.
Solution Approach 2:
The system dynamically changes compression parameters based on data content characteristics. Instead of using fixed compression settings for all data, the system extracts feature amounts from each data file, matches them with reference features, and automatically adjusts compression format and parameters to match the specific characteristics of the data being compressed, thereby optimizing compression效果 for each case.
Data Source
AI summary
A purpose of the present invention is to easily select an appropriate processing format, an appropriate parameter, or the like by predicting a process result that varies according to content of data before executing the process.According to the present invention, provided is an information processing device including: a feature amount extraction unit configured to extract a feature amount of data serving as a target of a process; a feature amount matching unit configured to match the feature amount with one or more reference feature amounts associated with a prediction result of the process in a database; and a result prediction unit configured to predict a result obtained in a case where the process is executed for the data, on the basis of a result of the matching.