User-Based Standing Query Execution with Geographical Context
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Solution Overview
Problem
Existing systems lack the ability to automatically generate and execute standing queries with geographical context based on user location or history, leading to inefficient information delivery to users.
Innovation Solution
A computer-implemented method and system that determines a user's location and identifies matching standing queries with geographical context, executing them to provide relevant search results and notifications, with options for triggers like time, user action, or frequency, and filtering to prevent unnecessary notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If standing queries are executed continuously or frequently to provide updated information to users, then information freshness is improved, but system resource consumption and user notification fatigue increase
Solution Approach 1:
The system executes standing queries periodically at scheduled intervals rather than continuously, allowing users to specify execution frequency (e.g., daily, weekly, monthly). This periodic execution maintains information freshness while significantly reducing system resource consumption compared to continuous monitoring.
Solution Approach 2:
The system monitors user interactions and location data to dynamically adjust query execution. When users are detected to be near relevant locations or show interest in query topics, the system increases execution frequency. This feedback mechanism ensures information is delivered when most valuable while avoiding unnecessary executions during low-interest periods.
2Adaptability or versatility
If standing queries are customized for each user based on their location and history to improve relevance, then information relevance is improved, but system complexity increases
Solution Approach 1:
The system pre-processes user data including location history, search patterns, and preferences to build user profiles in advance. When a standing query is created or executed, the system retrieves pre-computed user characteristics rather than analyzing raw data in real-time. This preliminary action enables高度 customized query results while keeping the execution complexity low.
Solution Approach 2:
The system creates simplified copies or representations of user profiles and query parameters that can be quickly matched and compared. Instead of performing complex analytical computations during query execution, the system uses pre-generated user profiles and location fingerprints that enable fast relevance matching through simple comparison operations.
3Ease of operation
If standing queries include geographical parameters to provide location-based information, then user experience is improved, but query execution time and processing load increase
Solution Approach 1:
The system pre-computes and stores geographical context data including location boundaries, point-of-interest metadata, and spatial relationships in advance. When a standing query with geographical parameters is executed, the system queries these pre-processed spatial indexes rather than performing complex geometric calculations in real-time, dramatically reducing execution time.
Solution Approach 2:
The system replaces complex real-time geographical computations with pre-computed spatial indexes and cached location data. Instead of calculating distances, boundaries, and spatial relationships during query execution, the system uses pre-generated geographical context that can be quickly retrieved and matched, substituting heavy mechanical computation with efficient data lookup.
Data Source
AI summary
Computer-implemented methods for generating and executing user-based standing queries are provided. In one aspect, a method includes determining whether to generate a notification based on a user-based query and geographical context. The method also includes filtering the notification through explicit or inferred filter criteria. Systems and machine-readable media are also provided.