Geographic Feature Query Offset Detection for Content Targeting
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Solution Overview
Problem
Current search systems fail to effectively target content to geographic features with similar query patterns but offset in time, leading to inefficiencies in ad campaigns and content delivery.
Innovation Solution
A method that determines excess queries for a target geographic feature, identifies candidate features with similar excess queries but displaced in time, and targets content using a time offset based on the similarity and quality of these queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is targeted to geographic features based on current query patterns, then content relevance to current user interests is improved, but opportunities to reach users with similar interests in other geographic areas at different times are lost
Solution Approach 1:
The system performs preliminary analysis of query patterns to identify geographic features with similar excess queries displaced in time. By determining time offsets between target and candidate geographic features based on historical query patterns, the system prepares targeting information in advance, enabling content to be delivered to candidate geographic features at the appropriate future time when user interest is likely to occur.
2Productivity
If content targeting is expanded to include similar geographic features with temporal offsets, then content delivery effectiveness is improved, but system complexity increases
Solution Approach 1:
The system segments the problem by first identifying excess queries for a target geographic feature, then separately determining candidate geographic features with similar excess queries displaced in time. The process divides complexity into manageable steps: determining excess queries, finding similar geographic features, calculating time offsets, and finally targeting content. This segmented approach reduces overall system complexity while achieving comprehensive content targeting.
Solution Approach 2:
The system uses excess query patterns as an intermediary to bridge target and candidate geographic features. By analyzing excess queries and their temporal displacement, the system creates a mediator relationship that connects geographic features with similar user interests but different temporal patterns, enabling indirect content targeting without requiring direct real-time user behavior data from candidate locations.
3Measurement precision
If the system analyzes query patterns across multiple geographic features and time periods, then accuracy of content targeting is improved, but computational resources required increase
Solution Approach 1:
The system extracts only the necessary information from query pattern data by focusing specifically on excess queries rather than analyzing all queries. By identifying and extracting excess query patterns from target geographic features and comparing them with candidate geographic features, the system reduces the volume of data that requires computational processing while maintaining high targeting accuracy.
Solution Approach 2:
The system applies partial action by determining excess queries for specific time periods rather than analyzing all historical data continuously. By comparing geo-query counts to expected query counts and identifying only excessive patterns, the system performs targeted analysis rather than comprehensive processing of all query data, reducing computational energy consumption while maintaining precision.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, including a method that comprises: determining excess queries for a target geographic feature, where the geographic feature defines a location; determining one or more candidate geographic features that have similar excess queries, but displaced in time; determining a time offset between the target geographic feature and a candidate geographic feature based on the displacement in time of the similar excess queries; and targeting content to the candidate geographic feature using the time offset and based on content targeted to the target geographic feature.