Context-Based Journey Purpose Analysis for Map Stop Suggestions
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Solution Overview
Problem
Conventional map applications require users to specify interests for displaying points of interest along routes, limiting their ability to automatically suggest relevant stops based on the purpose of the journey, which may not be accurately determined without user input.
Innovation Solution
A map application performs context-based analysis using destination information, calendars, social media, and historical data to determine the purpose of a journey, then suggests and displays relevant stops on the map without user specification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the map application requires users to specify interests for displaying points of interest, then the user has control over what is displayed, but the application cannot automatically determine the purpose of the journey
Solution Approach 1:
The system performs preliminary analysis of calendar events, social media data, and historical trip information before the user requests route information. This pre-processing of context data enables the system to automatically determine journey purpose without requiring users to manually specify interests, resolving the contradiction between accurate purpose determination and ease of operation
Solution Approach 2:
The map application autonomously analyzes multiple data sources including calendar applications, social media platforms, and historical trip data to self-determine the purpose of the journey. This self-service capability eliminates the need for explicit user input while maintaining high accuracy in identifying journey context, such as detecting business meetings from calendar events or leisure activities from social media posts
2Quantity of substance
If the map application displays all possible points of interest along the route, then the user has comprehensive information, but the information becomes overwhelming and less relevant
Solution Approach 1:
The system applies local quality by tailoring the displayed points of interest to the specific journey context identified through analysis of calendar events, social media, and historical data. Instead of uniformly displaying all POIs, the system selectively presents stops that are locally relevant to the detected journey purpose, such as suggesting business-related stops for work trips and leisure stops for personal travel, thereby maintaining high relevance while providing appropriate quantity of suggestions
3Measurement precision
If the map application performs context-based analysis using multiple data sources, then the journey purpose can be accurately determined, but the system complexity increases
Solution Approach 1:
The system introduces intermediary components that act as mediators between multiple data sources and the core routing functionality. These intermediaries include calendar analysis modules, social media integration layers, and historical data processors that translate diverse data formats into standardized journey context information. This intermediary architecture enables accurate purpose determination while managing system complexity by organizing data flow and processing logic in modular fashion
Data Source
AI summary
A map application includes a mechanism to perform context-based analysis to determine the purpose of a journey. The context-based analysis can include an analysis of any or all of the following: the destination, one or more calendars, social media, and historical data. Once the context-based analysis determines the purpose of the journey, the map application suggests one or more stops based on the purpose of the journey, and displays the suggested stop(s) on the map displayed to the user.