Geographically Local Query Detection via Geo-Query Count Thresholds
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Solution Overview
Problem
Search systems often fail to adequately emphasize local search results for users in specific geographic regions, leading to user dissatisfaction when local queries are not properly identified and prioritized.
Innovation Solution
A method that analyzes search query logs to determine geo-query counts for specific regions, compares these counts to expected query counts, and adjusts initial result scores for local search results using a boost factor when the query count exceeds the expected count by a threshold, thereby prioritizing local search results in search results presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the search system provides local search results for all queries, then user satisfaction in regions with local attractions improves, but search result relevance for queries without local significance deteriorates
Solution Approach 1:
The patent applies local quality by making the search result presentation adaptive to different geographic regions. The system determines whether a query has local significance in a particular region and adjusts the presentation accordingly - emphasizing local search results for regionally significant queries while maintaining standard presentation for non-local queries. This resolves the contradiction by applying local enhancement only where appropriate rather than universally.
Solution Approach 2:
The system dynamically adjusts search result presentation based on real-time analysis of query patterns and geographic data. By continuously monitoring whether query counts exceed expected thresholds for specific regions, the system adaptively determines when to emphasize local results versus standard results, resolving the static contradiction between local and global search needs.
2Ease of manufacture
If the search system emphasizes local search results for all queries, then local points of interest are highlighted, but the accuracy of identifying truly local queries deteriorates
Solution Approach 1:
The system performs preliminary analysis by comparing actual query counts against pre-established expected query count thresholds for different geographic regions. This pre-computed baseline approach allows the system to accurately identify queries with local significance before presenting results, improving classification precision while maintaining ease of local result emphasis.
Solution Approach 2:
The system uses feedback from query pattern analysis to continuously refine its identification of local queries. By monitoring whether actual query counts exceed expected thresholds and observing user interactions with search results, the system adjusts its classification accuracy over time, resolving the contradiction between ease of emphasis and measurement precision.
3Reliability
If the search system analyzes query logs to identify local queries, then local search results are accurately identified, but system complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for local query identification - comparing query counts against expected thresholds for specific geographic regions. By focusing on this single key metric rather than analyzing all possible query characteristics, the system achieves reliable local query identification while minimizing the added complexity of the analysis system.
4Ease of operation
If the search system adjusts result scores for local search results, then local results are prioritized in presentation, but the complexity of result ranking increases
Solution Approach 1:
The system changes the ranking parameter by applying a boost factor to local search results when a query is identified as having local significance. This simple parameter adjustment - multiplying the relevance score by a boost factor - achieves easy local result prioritization while adding minimal complexity to the ranking system, as it builds upon existing relevance scoring mechanisms.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting local search queries. In one aspect, a method includes accessing a search query log that includes data specifying search queries corresponding to particular geographic regions and for at least one of the search queries corresponding to the particular geographic region generating a geo-query count that represents a total number of times that the search query was received over a specified period. The geo-query count is compared to a corresponding expected query count for the search query, where the expected query count is a baseline number of times that the query is expected to be received. In response to determining that the search query has a geo-query count that exceeds the corresponding expected query count by at least a threshold amount, the particular query is classified as a local query for the particular geographic region.