Venue Profile Characterization via User Visit Data
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Solution Overview
Problem
Current technologies provide incomplete information about venues, lacking demographic details and user behavior patterns, which hinders personalized decision-making for users and venues seeking to attract specific user groups.
Innovation Solution
Systems and methods that characterize venues based on user visit data, creating a structured user-visit-characterized venue profile incorporating temporal and behavioral patterns, which is updated dynamically to provide higher granularity and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If basic venue information from public directories and websites is used, then data availability is improved, but information completeness and granularity are worsened
Solution Approach 1:
The patent combines multiple data sources including public directories, websites, social media, and most importantly, user visit data from mobile devices. By merging these diverse sources, the system creates a comprehensive venue profile that includes both basic information and detailed user characteristics, thereby resolving the contradiction between data availability and information completeness.
Solution Approach 2:
The system introduces an intermediary processing layer that collects, aggregates, and analyzes user visit data from mobile devices. This intermediary component transforms raw user data into structured venue characteristics, enabling the system to overcome the limitations of public directories and websites by adding value through data processing and synthesis.
2Measurement precision
If detailed user visit data is collected and processed, then measurement precision and characterization accuracy are improved, but device complexity and processing requirements are worsened
Solution Approach 1:
The patent extracts only the necessary and relevant features from user visit data, such as visit frequency, time patterns, and user characteristics, rather than processing all raw data. This extraction approach maintains high measurement precision for venue characterization while reducing the overall processing complexity by focusing on key indicators.
Solution Approach 2:
The system applies different processing depths to different aspects of venue characterization. For example, it collects detailed temporal patterns for venues where precision is critical, while using coarser-grained data for less important attributes. This local quality approach optimizes the balance between accuracy and complexity by tailoring processing intensity to specific needs.
3Loss of information
If comprehensive user characteristics are analyzed, then information granularity is improved, but loss of time for data processing is worsened
Solution Approach 1:
The system performs preliminary processing and aggregation of user visit data in the background, before it is needed for venue characterization. By pre-computing user characteristics and visit patterns, the system reduces the time required for real-time analysis while maintaining comprehensive information granularity in the venue profiles.
Solution Approach 2:
The patent implements periodic updates to venue profiles based on accumulated user visit data. Instead of continuously processing all data in real-time, the system updates venue characteristics at scheduled intervals or when sufficient data has been collected, thereby reducing processing time while still providing granular information when needed.
Data Source
AI summary
Aspects of the technology described herein provide a personalized computing experience for a user based on a user-visit-characterized venue profile. In particular, user visits to a venue are determined. For those visits, user characteristics and/or visit characteristics are determined. User similarities and visit features similarities may be determined and associated with the venue to form the user-visit-characterized venue profile. The user-visit-characterized venue profile may be provided to an application or service such as a personal assistant service associated with the user, or may be provided as an API to facilitate consumption of the user-visit-characterized venue profile by an application or service.