Snippet Generation Using Content Feature Analysis
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Solution Overview
Problem
Conventional snippet generation methods often truncate search results at arbitrary boundaries, leading to reduced readability and understandability, making it difficult for users to determine the relevance or content of search results.
Innovation Solution
The system generates snippets based on content features and part-of-speech identification to align snippet boundaries with natural breaks in text, ensuring that significant content is not omitted, thereby providing users with higher quality information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If snippet length is constrained to maintain predetermined format, then snippet presentation consistency is improved, but snippet readability and understandability deteriorate due to arbitrary truncation
Solution Approach 1:
The patent segments the text at natural linguistic boundaries (sentence endings, paragraph breaks, semantic units) rather than applying uniform character-based truncation. This segmentation approach maintains presentation consistency through controlled snippet length while improving readability by avoiding arbitrary cuts within sentences or semantic units.
Solution Approach 2:
The system dynamically adjusts snippet generation parameters based on text features and boundary quality metrics. Instead of fixed-length truncation, the system varies snippet boundaries to align with natural text structures, changing the parameter of boundary position to simultaneously maintain length constraints and improve semantic coherence.
2Productivity
If conventional length-based truncation is used, then snippet length control is improved, but information completeness deteriorates by omitting significant content
Solution Approach 1:
The system performs preliminary analysis of text features and identifies optimal boundary positions before final snippet generation. By pre-identifying natural break points and semantic units, the system ensures that significant content is preserved while maintaining efficient generation through automated feature-based boundary selection.
Solution Approach 2:
The system uses feedback from text feature analysis and boundary quality evaluation to adjust snippet generation. By evaluating whether proposed boundaries preserve important content and maintain semantic coherence, the system refines boundary selection to minimize information loss while controlling snippet length.
Data Source
AI summary
Systems, methods, and computer storage media having computer-executable instructions embodied thereon that facilitate generation of snippets. In embodiments, text features within a keyword-sentence window are identified. The text features are utilized to determine break features that indicate favorability of breaking at a particular location of the keyword-sentence window. The break features are used to recognize features of partial snippets such that a snippet score to indicate the strength of the partial snippet can be calculated. Snippet scores associated with partial snippets are compared to select an optimal snippet, that is, the snippet having the highest snippet score.