Dynamic Location Search Query Update Mechanism
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search engines fail to provide real-time, geographically constrained results that adapt to a user's changing location, especially for users on the move, as they do not effectively update search queries based on new locations or travel objectives.
Innovation Solution
A method that receives a search query including a point of interest and current location from a client device, determines travel distance or time based on user-defined information, and updates search results by re-processing the location when the device's location changes, ensuring results remain within the defined proximity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If search engines provide static search results based on initial location, then device complexity is reduced, but adaptability to changing user location deteriorates
Solution Approach 1:
The system automatically monitors location changes and triggers search result updates without requiring user intervention. The client device or server continuously checks location data and autonomously determines when and how to refresh search results, making the system self-adaptive to location changes.
Solution Approach 2:
The system implements a feedback loop where location data is continuously monitored, compared against threshold criteria, and used to trigger appropriate actions (update search results or maintain current results). This closed-loop control enables dynamic adaptation while managing complexity through conditional logic.
2Loss of information
If search results are updated frequently to reflect location changes, then result relevance is improved, but loss of time increases
Solution Approach 1:
The system dynamically adjusts the frequency of search result updates based on location change magnitude. When location changes exceed a predefined threshold, updates are triggered; otherwise, current results are maintained. This dynamic approach ensures result relevance while minimizing unnecessary update operations that would consume time.
Solution Approach 2:
The system changes the parameter of update frequency based on the parameter of location change magnitude. By monitoring location displacement and comparing it against threshold values, the system adaptively determines whether to refresh search results, optimizing the balance between information freshness and time efficiency.
3Measurement precision
If location monitoring is continuous to maintain accurate search results, then measurement precision is improved, but use of energy increases
Solution Approach 1:
Instead of continuous monitoring, the system employs periodic location checks combined with threshold-based triggering. Location is monitored continuously at the hardware level, but processing and search result updates occur periodically only when location changes exceed the predefined threshold, reducing computational energy consumption while maintaining measurement precision.
Solution Approach 2:
The system maintains continuous location monitoring capability through the device's location services, but the useful action of processing and updating search results occurs only when necessary (when threshold is exceeded). This separates continuous data collection from periodic data processing, maintaining precision while reducing energy use for computation.
Data Source
AI summary
A method for identifying a result responsive to a current location of a client device includes receiving, form a client device and at a host, a search query that includes a point of interest and a current location of the client device. The method also includes automatically updating the search query as the current location of the client device changes and instructing the host to identify a potential location associated with the point of interest and located within a user-defined proximity from the current location of the client device.