Dynamic Snippet Generation for Search Results
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Solution Overview
Problem
Existing search engine snippet information generation methods are limited by fixed numbers of pictures and text lines, leading to incomplete key content display, unnecessary irrelevant content inclusion, and reduced user search efficiency.
Innovation Solution
A method and apparatus for dynamically generating and displaying snippet information based on detailed content and snippet attributes, such as line number, area size, and typesetting information, determined by key content matching the search content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If fixed numbers of pictures and text lines are used for snippet generation, then the snippet structure is simple and consistent, but the key content display becomes incomplete and irrelevant content is included
Solution Approach 1:
The patent applies dynamics by making the snippet attribute (number of text lines and pictures) variable rather than fixed. The system dynamically adjusts these attributes based on the actual content characteristics of each search result, allowing the snippet structure to adapt to different content types and lengths while maintaining optimal information display.
Solution Approach 2:
The patent changes the parameters of snippet generation from fixed values to content-dependent values. By determining snippet attributes (line count, picture count) based on key content analysis of each search result, the system optimizes the balance between information completeness and display constraints for each individual result.
2Loss of information
If more key content is displayed in the snippet, then user information acquisition improves, but the snippet area size and rendering complexity increase
Solution Approach 1:
The patent extracts only the key content from each search result based on content analysis, rather than displaying fixed portions of text. By identifying and extracting the most relevant information segments, the system maximizes information value within the available snippet display area without unnecessary content.
Solution Approach 2:
The patent applies local quality by making different parts of the snippet have different characteristics based on their importance. The system adjusts the number of text lines and pictures locally for each search result based on its content characteristics, allowing high-value content to receive more display space while maintaining overall layout consistency.
3Productivity
If snippet attributes are determined dynamically based on key content, then search efficiency improves, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary action by pre-analyzing the content characteristics of search results to determine key content segments before final snippet generation. This advance preparation allows the system to quickly assemble snippets without extensive real-time processing, reducing the perceived generation time for users.
Solution Approach 2:
The system performs self-service by automatically analyzing content and determining optimal snippet attributes without requiring manual intervention or complex external processing. The automated content analysis and attribute determination streamline the generation process while maintaining high customization for each result.
Data Source
AI summary
The present invention relates to a snippet information generation method and apparatus, a search result display method and apparatus, a device, and a medium. The search result display method includes: in response to search content, obtaining a first research result; displaying, in a search result page, snippet information corresponding to the first search result, wherein the snippet information is generated on the basis of detailed content and snippet attributes of the first search result, the snippet attributes comprise at least one of the snippet row number, the snippet area size, and snippet typesetting information, and the snippet attributes are determined on the basis of key content matched with the search content in the detailed content.