Search by Example Query Refinement via Metadata Display
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Solution Overview
Problem
Users face difficulties in constructing effective queries for search engines due to the need for knowledge of the dataset's content and structure, leading to a tedious, time-consuming, and error-prone process of refining search results.
Innovation Solution
A computer system that allows users to select and modify queries based on metadata from initial search results, displaying metadata in an easily understandable form and enabling users to incorporate it into the query to produce refined search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user manually reviews and refines search results multiple times, then the accuracy of search results is improved, but the time consumption and complexity of the search process increases
Solution Approach 1:
The system performs preliminary actions by automatically generating an initial query from user input, executing it to produce search results, and extracting metadata before the user needs to review anything. This preliminary processing reduces the user's workload and time required for subsequent refinement iterations.
Solution Approach 2:
The system implements feedback by displaying extracted metadata from search results to the user in a user-friendly format, allowing the user to review the metadata and provide corrections or additions. This feedback loop enables the user to refine the query based on actual search result characteristics without manually reviewing entire result sets.
2Measurement precision
If the user manually reviews search results to understand dataset structure, then the query accuracy is improved, but the ease of operation decreases
Solution Approach 1:
The system introduces metadata as an intermediary between the search results and the user. Instead of requiring the user to directly analyze search results to understand dataset structure, the system extracts and presents relevant metadata (field names, data types, constraints) that serves as a simplified representation, making it easier for users to construct accurate queries.
Solution Approach 2:
The system creates a simplified copy or representation of the dataset structure through metadata extraction. Rather than requiring users to examine actual search results to understand the data structure, the system generates a metadata model that copies the essential structural information in a more accessible format.
3Loss of information
If the system displays detailed metadata from search results, then the information completeness is improved, but the ease of understanding decreases for users not trained in annotation systems
Solution Approach 1:
The system applies local quality by selectively presenting different levels of metadata detail based on user needs and context. Rather than displaying all metadata uniformly, the system can present simplified views for general users while providing access to more detailed technical metadata for advanced users, optimizing both understandability and information completeness for different user groups.
Data Source
AI summary
A computer system uses a search engine to search a dataset using an initial query provided by a user and thereby to produce initial search results. The system enables the user to select portions of the initial search results. The system identifies metadata associated with the selected portions, and displays information representing that metadata in a form that is easily understandable by a person not trained in the annotation system in which the search results are encoded. The user may instruct the system to add one or more of the displayed metadata elements to the initial query, in response to which the system may add the specified metadata elements to the initial query to produce a modified query. The system may search the dataset using the modified query and thereby produce modified search results. The process may be repeated as desired by the user to further refine the search results.