Search Query Local Significance Detection
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Solution Overview
Problem
Search systems often fail to provide relevant local results for users submitting general search queries without location phrases, as they rely solely on global relevance rankings, potentially missing locally significant queries that require local information.
Innovation Solution
A method that detects locally significant search queries by analyzing user location and query frequency, creates a local search query by appending the user location to the general query, and combines general and local search results to prioritize locally relevant information in search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the search system provides only general search results based on global relevance rankings, then the search system maintains simplicity in result generation, but local significance is lost and user satisfaction decreases for location-specific queries
Solution Approach 1:
The search system pre-processes and stores locally significant queries and their associated geographic regions in a data structure before receiving search requests. When a query is received, the system quickly checks if it matches any pre-identified locally significant queries, enabling fast local result generation without complex real-time analysis
Solution Approach 2:
The search results are segmented into two distinct components: general search results and local search results. The system generates both types of results separately and then combines them, with local results given priority for locally significant queries. This segmentation allows the system to maintain both global relevance and local significance without requiring a complete redesign of the search algorithm
2Reliability
If the search system provides local search results for all general queries, then user satisfaction improves for local queries, but irrelevant local results are provided for non-local queries reducing overall accuracy
Solution Approach 1:
The system uses click-through data and user interaction patterns as feedback to continuously identify and update the set of locally significant queries. By monitoring which queries lead users to click on local results, the system refines its classification accuracy over time, ensuring that local results are provided only when they are actually desired by users
Solution Approach 2:
The system changes the parameter of query classification by identifying specific queries that have different meanings or significance in different geographic regions. Instead of applying a uniform local/results approach to all queries, the system dynamically adjusts which queries receive local treatment based on pre-analyzed significance patterns, maintaining precision while improving satisfaction
3Reliability
If the search system requests both general and local search results and combines them, then locally relevant information is prioritized in results, but the complexity of result processing and selection increases
Solution Approach 1:
The system applies different quality standards and ranking criteria to different portions of the search results. Local search results for locally significant queries are given priority placement and different ranking weightings compared to general results. This local quality approach ensures that locally relevant information is prominently displayed without requiring complex reprocessing of all results
Solution Approach 2:
The system merges general search results and local search results into a unified result set with a clear hierarchy. Local results are integrated into the general results framework rather than being completely separate, allowing the system to leverage existing ranking infrastructure while emphasizing local relevance. The merging process follows predefined rules that reduce processing complexity compared to completely independent ranking systems
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for servicing search queries. In one aspect, a method includes determining that a general search query is a locally significant query for a user location that is associated with the user general search query. In turn, a local search query is generated using the general search query and a location phrase representing the user location. A set of set of general search results responsive to the general search query and a set of local search results responsive to the local search query are requested. A final set of search results responsive to the search query are selected. The final set of search results include at least one search result that is included in the set of local search results, and is not included in a pre-specified quantity of highest ranking search results from the set of general search results. Data that cause presentation of the final set of search results are provided.