Search Gallery Expansion via Content Identifier Templates
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Solution Overview
Problem
Search engines face user frustration due to slow, inaccurate, and incomplete query results, leading to diminished user satisfaction and revenue, as users tend to abandon search engines that fail to deliver relevant information promptly and comprehensively.
Innovation Solution
The system expands galleries of query results by seeding them with seed query results, identifying a template from these results to map and include additional content identifiers, thereby enhancing the completeness and accuracy of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the search engine executes slowly, then users experience frustration and navigate to another search engine, but the search engine may deliver more thorough results
Solution Approach 1:
The system pre-generates and stores query results in galleries before users actually submit queries. When a user submits a query, the system checks if results already exist in the gallery and returns them immediately, eliminating the need for slow real-time execution while ensuring results are ready in advance
Solution Approach 2:
The system creates buffer galleries that store pre-computed query results as a cushion against potential execution delays. These pre-stored results act as a safety buffer that ensures fast response times and prevents user frustration even when new queries require substantial processing
2Measurement precision
If the search engine delivers query results which contain irrelevant information, then users experience frustration and navigate from one site to another, but the search engine may provide more comprehensive coverage
Solution Approach 1:
The system uses feedback from user interactions with query results to refine and update galleries. By analyzing which results users click on and which they ignore, the system continuously improves the relevance and precision of stored results while maintaining comprehensive coverage through iterative optimization
Solution Approach 2:
The system dynamically adjusts parameters such as relevance thresholds, weighting factors, and selection criteria based on performance data and user behavior patterns. This allows the system to optimize the balance between result relevance and comprehensive coverage by changing these parameters adaptively
3Loss of information
If the search engine delivers incomplete results, then users experience frustration as their search appears to have failed, but the search engine may reduce processing time
Solution Approach 1:
The system pre-computes and stores comprehensive query results in galleries before users need them. By performing the complete search operation in advance and caching the full results set, the system ensures that users receive complete information immediately without experiencing the time loss of waiting for comprehensive searches to execute
Solution Approach 2:
The system shifts from a single-dimension approach (executing searches in real-time) to a multi-dimensional approach by storing results across multiple galleries organized by different criteria. This allows the system to provide complete results quickly by retrieving from pre-computed galleries rather than executing new searches
Data Source
AI summary
Techniques and technologies for expanding a gallery by seeding the gallery with seed query results. A template is identified which is associated with the subjects of the seed queries and content identifiers are identified which include the template. These content identifiers are used to expand the gallery to include more content identifiers than before the expansion of the gallery.