Dataset Analysis Pattern Recommendation for Non-Expert Users
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Solution Overview
Problem
Existing data analysis tools require users to have advanced skills and involve time-consuming manual operations for dataset analysis, making it difficult for non-experts to efficiently analyze datasets.
Innovation Solution
An automatic analysis recommendation system that extracts dimension and operation features from datasets, determines suitable analysis patterns using machine learning models, and provides recommendations for analysis operations, allowing users to quickly complete data analysis tasks without extensive knowledge of the tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data analysis operations are used, then analysis flexibility and control are improved, but user expertise requirements increase and time consumption increases
Solution Approach 1:
The system performs self-service by automatically extracting features from datasets, generating analysis patterns, and recommending analysis operations without requiring user intervention. The analysis recommendation module autonomously processes datasets and outputs analysis recommendations, eliminating the need for users to manually configure analysis parameters or understand complex analysis workflows.
Solution Approach 2:
The system performs preliminary actions by pre-extracting dimension features and operation features from datasets before analysis is requested. The feature extraction module prepares feature information in advance, and the analysis pattern generation pre-computes candidate analysis patterns, so that when users request analysis, the system can quickly provide recommendations without time-consuming manual operations.
2Adaptability or versatility
If advanced analysis tools are used, then analysis capability is improved, but user expertise requirements increase
Solution Approach 1:
The system introduces an intermediary layer between users and complex analysis tools. The analysis recommendation module acts as a mediator that translates user requests into appropriate analysis operations by selecting from pre-generated analysis patterns. This intermediary layer shields users from the complexity of advanced analysis tools while still providing access to sophisticated analysis capabilities.
Solution Approach 2:
The system creates simplified copies of complex analysis operations in the form of pre-generated analysis patterns. Instead of requiring users to understand and configure complex analysis parameters, the system provides copy-ready analysis patterns that encapsulate sophisticated analysis logic, which users can directly apply to their datasets.
3Productivity
If automated analysis recommendation is implemented, then ease of operation is improved and time loss is reduced, but system complexity increases
Solution Approach 1:
The system segments the complex analysis process into distinct modular components: a feature extraction module that extracts dimension and operation features, an analysis pattern generation module that creates candidate patterns, and an analysis recommendation module that selects and recommends patterns. This segmentation allows each module to handle specific tasks independently, managing overall system complexity while maintaining high productivity.
Data Source
AI summary
According to implementations of the subject matter described herein, there is provided a solution for automatic recommendation of analysis for a dataset. In this solution, dimension feature information of dimensions of a dataset and operation feature information of candidate analysis operations are extracted. Respective metrics of candidate combinations of the dimensions and candidate analysis operations being suitable for defining an analysis pattern for the dataset are determined based on the dimension and operation feature information. The analysis pattern comprises at least one dimension to be analyzed and at least one analysis operation to be performed on the at least one dimension. A recommendation on an analysis pattern for the dataset is provided based on the determined respective metrics, to indicate a candidate combination. In this way, it is possible to assess and provide a suitable analysis pattern for a given dataset, thereby facilitating quick completion of the data analysis task.