Group Meet-up Venue Recommendation System with Location-Based Filtering
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Solution Overview
Problem
Existing methods for locating and ranking potential meeting venues for a group of users are limited to small geographic areas and do not effectively filter or rank venues based on desirability, leading to lengthy discussions and debates.
Innovation Solution
A system that allows users to create a 'meet-up' request, shares it with contacts, and uses geographic location data to identify, score, filter, and rank potential venues based on collective preferences, allowing for a vote to determine the most suitable location, which also provides arrival times and digital business card details for the selected venue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If venue selection is done without automated filtering and ranking, then users can see all potential venues, but the process requires lengthy discussions and debates
Solution Approach 1:
The system performs preliminary filtering and ranking of venues based on group members' locations and preferences before presenting options for voting. This preliminary action eliminates the need for lengthy discussions by pre-processing venue data according to objective criteria such as proximity to participants and venue characteristics.
Solution Approach 2:
The automated venue selection system acts as an intermediary between raw venue data and user decision-making. It introduces an intermediate processing stage that filters and ranks venues based on multiple factors, reducing the complexity of the decision process and minimizing the time required for group discussions.
2Adaptability or versatility
If the system covers only small geographic areas, then venue location calculations are simpler, but the system cannot support meetings in larger areas
Solution Approach 1:
The system segments the geographic area into manageable zones and processes venue selection for each zone independently. By dividing the larger geographic area into smaller sub-areas, the system can handle complex spatial calculations without becoming overwhelming, allowing it to scale from small to large geographic coverage.
Solution Approach 2:
The system transitions from considering only proximity distance to incorporating multiple spatial dimensions and venue attributes. By adding dimensions such as venue type, capacity, and member preferences to the spatial calculation, the system can effectively handle larger geographic areas while maintaining relevance to user needs.
3Measurement precision
If all potential venues are presented to users without filtering, then users have complete information, but users cannot identify the most desirable venues efficiently
Solution Approach 1:
The system changes the parameters used to evaluate venues from simple distance-based metrics to a multi-parameter scoring system that includes venue characteristics, group member preferences, and location factors. This transformation allows the system to precisely assess venue desirability while presenting a manageable ranked list to users.
Solution Approach 2:
The system incorporates feedback from group member preferences and voting behavior to refine venue recommendations. By using feedback mechanisms, the system learns from user responses and improves its ability to identify desirable venues, making the selection process both accurate and easy to use.
Data Source
AI summary
Disclosed are methods and systems for locating, filtering, ranking and then providing a selection of potential “meet-up” venue(s) and time(s) recommendations to a group of users of a device having an interface and a display (e.g., a smart phone or a tablet) based on the geographic area delineated by a user and the user's contacts who are invited to the “meet-up”. The methods and systems calculate, filter and rank the most convenient “meet-up” venue and time based on the current location of group members, taking into account a plurality of factors, such as time, distance, schedule, group member's interests, availability, and the like. The methods and systems then provide a selection of the top ranking “meet-up” venues to the group members. Thereafter, the group members vote for the most suitable location among the ranked “meet-up” venues.