User Interest Profile Generation via Location-Based Check-In Analysis
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Solution Overview
Problem
Existing internet-based social networks fail to accurately identify and connect individuals and organizations with similar interests at a local level, leading to inefficient targeted advertising and community service planning due to poorly defined interest groups and lack of geographical context.
Innovation Solution
A method and system that generate user interest profiles by analyzing interactions with activities at specific locations within a geographical area, combining internet communication capabilities with mobile application data to categorize and score user interests as positive, zero, or negative, creating a database for targeted advertising and social networking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If internet-based social networks are used for targeted advertising, then communication reach is improved, but accuracy of identifying user interests deteriorates
Solution Approach 1:
The patent transitions from traditional online-only social networking to a multi-dimensional system that integrates both online interactions and offline geographical location data. By adding the spatial dimension through mobile device GPS coordinates and venue check-ins, the system creates a more comprehensive profile of user interests that combines digital behavior with physical world patterns, thereby improving interest identification accuracy while maintaining broad communication reach
Solution Approach 2:
The patent introduces mobile devices and location-based services as intermediaries between users and the social networking system. These intermediaries capture geographical context and venue information, serving as a bridge that translates physical world behaviors into digital profiles, thus enhancing the precision of interest identification without compromising the extensive reach of internet-based communication
2Ease of operation
If location-based websites allow users to check-in at venues, then user engagement is improved, but ability to identify true user interests deteriorates
Solution Approach 1:
The patent merges multiple data sources including venue check-in information, mobile device location data, user interactions with activities, and contextual information from various websites. By combining these diverse data streams into a unified interest profile system, the patent overcomes the limitation of relying solely on self-reported user interests or simple check-in data, thereby improving the accuracy of interest identification while maintaining high user engagement through easy check-in functionality
Solution Approach 2:
The patent implements a feedback mechanism where user behavior patterns across multiple venues and time periods are continuously analyzed to refine interest profiles. The system processes recurring visit patterns, time spent at venues, and interactions with activities to generate feedback that progressively improves the accuracy of interest identification, transforming simple check-in data into reliable interest indicators while keeping the user experience engaging and straightforward
3Adaptability or versatility
If social networks collect detailed user information, then personalization is improved, but data processing complexity deteriorates
Solution Approach 1:
The patent segments the complex data processing task into distinct modular components: mobile device identification module, location data extraction module, venue check-in processing module, activity interaction analysis module, and interest profile generation module. Each module handles a specific aspect of data processing independently, reducing overall system complexity while enabling detailed personalization through comprehensive data analysis. This segmented architecture allows the system to process diverse information sources without becoming unmanageably complex
Data Source
AI summary
At least one application is executable to communicate with a check-in service configured to receive check-in data comprising identification data of the user of at least one application executable on or accessible via an electronic device, location data of a venue for which the user is able to perform a check-in event via said application or said service, and time data for the check-in event indicative of when the check-in event took place. The check-in data is obtained and then analyzed to identify at least one activity taking place within the given geographical area and at least one corresponding venue within the given geographical area. At least one corresponding venue with regard to the corresponding at least one activity is categorized. The interest profile is generated or amended by the user based on the step of analysing. The interest profile comprises data of the user's interaction with the at least one activity corresponding to the at least one venue.