Search Result Linking for Query-Aware Access and Confidence Display
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional search systems struggle to provide relevant and confident results when users query structured or unstructured datasets, as they often fail to identify the most appropriate dataset type for the query and lack customization in result presentation.
Innovation Solution
A computing system determines whether to query structured or unstructured datasets based on query entities and user preferences, and customizes result presentation with confidence scoring and expansion/collapse mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional search systems query both structured and unstructured datasets without selection, then more comprehensive results are obtained, but system complexity and query processing time increase
Solution Approach 1:
The search system is segmented into multiple independent components: a query analyzer that determines dataset type, separate structured and unstructured search engines, and a result merger. This segmentation allows each component to specialize in specific tasks, improving reliability while managing complexity through modular architecture.
Solution Approach 2:
The system performs preliminary analysis of the query to determine whether it targets structured or unstructured data before executing the search. This preliminary classification action prevents unnecessary querying of inappropriate dataset types, reducing system complexity and improving result relevance by ensuring the right search engine handles each query.
2Reliability
If traditional search systems present all search results equally, then completeness is maintained, but user ability to identify confident results decreases
Solution Approach 1:
The search results are differentiated by applying local quality indicators - specifically confidence scores - to each individual result. High-confidence results receive distinctive visual treatment (such as expanded display or special formatting), while lower-confidence results are presented differently. This allows users to quickly identify reliable information without obscuring less certain results, maintaining completeness while improving ease of operation.
3Loss of information
If search results are expanded by default to show all details, then information completeness is improved, but information overload and processing time increase
Solution Approach 1:
The search result presentation is made dynamic and adaptive based on result confidence. High-confidence results are automatically expanded to show full details, while lower-confidence results are collapsed or summarized. Users can interact with the interface to expand or collapse results as needed. This dynamic adaptation reduces initial information overload for users while ensuring complete information is available when confidence warrants it, balancing information completeness with user processing time.
Data Source
AI summary
In general, the subject matter described in this disclosure can be embodied in methods, systems, and program products for linking to a search result. A computing system receives a query and provides, to a first computing device, multiple results that are responsive to the query. The computing system provides, to the first computing device, information that identifies a web address of a user selected result of multiple results that are responsive to query. The computing system receives a request from a second computing device for content responsive to the web address of the user selected result. The computing system provides, to the second computing device, information to cause the second computing device to present the multiple results that are responsive to the query in distinction to the user selected result, responsive to the second computing device not being authorized to access the user selected result.