Location-Based Similarity Search Using Feature Vectors
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Solution Overview
Problem
Users are deterred from utilizing location-based services due to the complexity and inconvenience of inputting various data requirements, making it difficult for service providers to offer efficient and convenient navigation and local search services.
Innovation Solution
A method and system that allows users to specify a reference point-of-interest, generating a list of similar points-of-interest in a selected region by using feature vectors and weighting vectors to determine similarity scores, thereby simplifying the search process and providing quick and efficient results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are required to input various data requirements for location-based services, then the services can provide comprehensive and accurate results, but the complexity and inconvenience increase, deterring users from utilizing the services
Solution Approach 1:
The system automatically determines the user's current location using GPS or other location services without requiring manual input. The user simply activates the service, and the system self-configures the search parameters based on the obtained location data, eliminating the burden of data entry while maintaining accurate location-based search results
Solution Approach 2:
The system pre-loads and stores information about multiple points of interest including restaurants, hotels, and other establishments with their locations, categories, and attributes. When a user activates the service, the search results are quickly generated from pre-processed data, providing comprehensive results without requiring the user to input search criteria
2Adaptability or versatility
If the system provides comprehensive location-based services with multiple input requirements, then the service functionality is enhanced, but the device complexity and operational difficulty increase
Solution Approach 1:
The system provides a unified location-based service interface that handles multiple types of searches (restaurants, hotels, attractions, etc.) through a single activation. The same core mechanism obtains user location and retrieves relevant points of interest regardless of category, eliminating the need for separate input requirements for different service types while maintaining comprehensive functionality
Solution Approach 2:
The system introduces an intermediary processing layer that automatically translates the user's location data into relevant search queries. This intermediary component handles the complexity of data processing, category filtering, and result ranking, shielding the user from system complexity while delivering versatile service results
3Measurement precision
If users must provide extensive input data for navigation and local search services, then the search results can be more precise, but the time and effort required increases
Solution Approach 1:
The system continuously monitors and updates the user's location data in the background and pre-organizes points of interest by location and category. When the user activates the service, the system immediately retrieves relevant results from pre-processed data structures, eliminating the time required for data entry and initial processing while maintaining precise location-based search results
Data Source
AI summary
An approach is provided for determining the similarity between a reference point-of-interest and similarity candidate points-of-interest. Data specifying a reference point-of-interest and location data of a search region are received. A reference vector specifying a plurality of features associated with the reference point-of-interest is retrieved. A plurality of candidates for similar points-of-interest are determined based, at least in part, on the search region. A similarity score is determined for each of the candidates. A list of one or more similar points-of-interest is generated based on the similarity scores.