Display Search Interface for Local and Cloud Result Integration
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Solution Overview
Problem
Existing electronic devices provide limited search results based on locally stored data, resulting in a small search range and insufficient content.
Innovation Solution
The electronic device obtains search results from both local storage and a server, categorizing and displaying them in separate areas based on type, with prioritization based on weight and user behavior, to enhance search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If search results are obtained only from local storage, then device complexity is reduced, but search range and content quantity are limited
Solution Approach 1:
The search system is segmented into two independent parts: local search module and cloud search module. Each module operates independently to search different data sources (local storage and server respectively), then the results are merged. This segmentation allows the system to access both local and cloud data without requiring complete system redesign, thus increasing search content while managing complexity through modular architecture.
Solution Approach 2:
The patent merges search results from local storage and server by categorizing them into different display areas (first area for local results, second area for cloud results). This merging approach consolidates search functionality while maintaining clear separation of data sources, enabling users to access comprehensive search results from both local and cloud sources simultaneously.
2Ease of operation
If search results from local and server are displayed separately, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The display area is segmented into distinct first and second areas, with the first area displaying local search results and the second area displaying server search results. This segmentation makes it easy for users to identify and access results from different sources without confusion. The segmentation is implemented through clear spatial separation in the user interface, requiring minimal processing complexity while significantly improving user experience.
3Productivity
If search results are prioritized based on weight and user behavior, then search efficiency is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary action by pre-defining weight values for different search result types (local results, server results, combined results) and pre-establishing prioritization rules based on user behavior patterns. When a search query is executed, the system simply applies these pre-established weights and rules to sort and display results, rather than performing complex real-time analysis. This preliminary preparation significantly improves search efficiency while keeping processing complexity manageable.
Data Source
AI summary
The electronic device obtains a first search result and a second search result from a server based on the search word. The electronic device retrieves, based on the search word, in data stored in the electronic device to obtain a third search result. The first search result and the third search result belong to a same type, and the second search result and the first search result belong to different types. The electronic device displays a search result page, where the search result page includes a first area and a second area, the first area displays the first search result and the third search result, and the second area displays the second search result.