Meeting Location Selection Using Geospatial and Preference Data
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Solution Overview
Problem
Existing systems for coordinating meetings between users of mobile communications networks do not effectively utilize real-time geospatial location and user preferences to suggest relevant meeting locations, lacking integration of users' interests and historical activities in the selection process.
Innovation Solution
A system that identifies users' current geospatial locations and preferences by parsing user input, utilizing a meeting coordination service to select a meeting location based on the detected keywords, interests, historical activities, and preferences, and transmitting the proposed location to the users' mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If meeting location selection is based solely on current geospatial location, then the system is simple to operate, but the suggested locations do not reflect user preferences or interests
Solution Approach 1:
The system automatically extracts user preferences and interests from unstructured communication data without requiring explicit user input or configuration. The server autonomously analyzes chat messages, emails, or other communications to identify relevant keywords, categories, and historical patterns, then uses this information to select meeting locations that align with user preferences while maintaining ease of use.
Solution Approach 2:
The system transforms raw communication data into structured preference parameters by parsing keywords, identifying categories (e.g., dining, entertainment), and extracting historical activity patterns. These transformed parameters are then used to dynamically select meeting locations, enabling the system to adapt to user preferences without adding operational complexity.
2Manufacturing precision
If the system analyzes user input to identify categories and preferences, then the relevance of suggested locations improves, but the processing complexity increases
Solution Approach 1:
The server acts as an intermediary between raw user communications and location selection. It receives unstructured data (chat messages, emails), processes it through keyword extraction and category identification algorithms, and outputs structured preference information that drives location recommendations. This intermediary processing layer handles the complexity centrally without affecting client device simplicity.
Solution Approach 2:
The system replaces manual location selection mechanisms with automated computational analysis. Instead of requiring users to explicitly specify preferences or manually search for locations, the system uses natural language processing and pattern recognition to automatically identify user preferences from communication data and select appropriate locations.
3Reliability
If the system uses historical information and user preferences to select locations, then the satisfaction with suggested locations improves, but the time required for location selection increases
Solution Approach 1:
The system continuously collects and stores historical communication data and user activity patterns in advance, building a knowledge base of user preferences before the actual meeting coordination is needed. When a meeting is requested, the system queries this pre-processed historical information to quickly generate location recommendations, avoiding the need for real-time analysis of extensive historical data.
Solution Approach 2:
The system selectively processes only the most relevant portions of historical data and communication history rather than analyzing all available information comprehensively. By identifying key keywords and prominent preferences from vast amounts of data, the system generates reliable location recommendations efficiently, balancing thoroughness with processing time.
Data Source
AI summary
Systems and methods are provided to coordinate meetings between users of mobile devices on a mobile communications network. Users of the mobile communication network send one another meeting invitations over the network. The system receives the current geospatial position of one or more such users, as well as category selections that relate to attributes of potential meeting locations meetings. The system selects meeting locations for users using the current geospati.al positions of the users and the category selections such that meeting locations are located at a geospati.al positions between the users. The system can additionally select meeting locations that factor in user preferences and historical activities.