Location-Based User Matching Using Shared Place History
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Solution Overview
Problem
Existing matching services struggle with irrelevant search results and fail to incorporate non-textual criteria in determining compatible matches, making it challenging to link individuals with similar character traits and values.
Innovation Solution
A system and method that utilizes location information to match users by analyzing historical location data and preferences, presenting relevant matches based on shared locations and characteristics, using a database to correlate location data with points-of-interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If matching services use only textual submissions (profiles or messages) to determine matches, then the matching process is simple to implement, but the matching relevance and accuracy deteriorate because non-textual criteria that users actually use for evaluation are not incorporated
Solution Approach 1:
The patent introduces location information as an additional dimension beyond textual profiles. By incorporating spatial data (coordinates, location history, points of interest visited) into the matching algorithm, the system evaluates users based on where they have been, creating a multi-dimensional matching framework that combines textual and spatial criteria for more accurate match recommendations
Solution Approach 2:
The patent uses location information as an intermediary factor to bridge the gap between user profiles and match recommendations. Instead of directly comparing textual profiles, the system uses shared locations and location patterns as a mediator to identify potential matches, thereby improving accuracy while maintaining manageable system complexity through a clear intermediary matching mechanism
2Quantity of substance
If matching services include comprehensive search results, then more potential matches are available, but the search results contain many irrelevant entities which costs user time and deters continuation
Solution Approach 1:
The patent performs preliminary filtering by incorporating location information into the matching criteria before generating match recommendations. By pre-evaluating users based on shared locations and location patterns, the system filters out irrelevant entities early in the process, presenting only those users who have visited similar places, thereby reducing the number of irrelevant results users must review and saving user time
Solution Approach 2:
The patent applies local quality by making matching criteria specific to location-based characteristics. Instead of uniform matching across all users, the system tailors match recommendations to users' actual visited places and location patterns, ensuring that each user receives matches relevant to their specific location history rather than generic matches
3Reliability
If matching services coordinate relationships between like-minded individuals, then match quality improves, but the coordination process becomes a significant chore with numerous obstacles and barriers to overcome
Solution Approach 1:
The patent implements self-service by allowing location information to automatically indicate compatibility between users. Instead of requiring users to manually coordinate or specify detailed preferences, the system uses users' own location history and visited places as automatic indicators of potential match quality, eliminating the need for complex coordination while maintaining high match quality through passive data collection and automated matching
Data Source
AI summary
In one embodiment, a method executed by at least one processor includes receiving first historical location information identifying a first location area at which a first user was present at a first time and receiving second location information identifying a second location area at which a second user was present at a second time. The method includes determining that the first historical location information and the second location information each correspond to a particular location area and determining that a characteristic related to the first user corresponds to a preference related to the second user. In response to these determinations, the method includes causing information related to the first user to be presented to the second user. The information related to the first user includes the first location area of the first user relative to the second location area of the second user.