Activity Context Graph for User Activity Tracking
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Solution Overview
Problem
Existing systems fail to effectively manage and track user activities across multiple sessions and devices, leading to inefficiencies in resource management and collaboration, as they lack a comprehensive method to monitor, analyze, and visualize user interactions with various resources.
Innovation Solution
A computer system and method that monitors user actions, identifies activities, and generates an activity context graph, which includes information about resources accessed, relationships between them, and allows for easy access and sharing, enabling efficient tracking and collaboration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing systems are used to track user activities, then basic monitoring is possible, but comprehensive tracking across multiple sessions and devices is ineffective
Solution Approach 1:
The system segments user activity tracking into discrete actions and resources, representing them as nodes in a graph structure. Each user action (e.g., clicking, scrolling, selecting) is broken down into individual trackable events, and each resource (e.g., documents, websites, files) is segmented as a separate entity. This segmentation enables comprehensive tracking across multiple sessions and devices by creating granular, independent units that can be reliably monitored and reassembled into complete activity contexts.
Solution Approach 2:
The activity context graph serves as an intermediary data structure that bridges user actions and resources. The graph captures relationships between actions and resources as edges, creating a mediator layer that preserves the context and connections between disparate activity elements. This intermediary representation allows the system to maintain reliable tracking information across sessions and devices by storing the contextual relationships in a structured format that can be queried and reconstructed.
2Loss of information
If comprehensive monitoring of user actions and resources is implemented, then complete activity context is captured, but system complexity increases
Solution Approach 1:
The activity context graph serves multiple functions within a single unified data structure. It simultaneously stores user actions, resources, relationships between them, temporal sequences, and contextual metadata. The graph structure itself provides multiple capabilities: node identification, relationship mapping, path traversal for sequence reconstruction, and filtering for specific activity types. This multi-functionality reduces system complexity by consolidating what would otherwise require multiple separate tracking systems into a single versatile framework.
Solution Approach 2:
The system changes the parameter representation of activity data by transforming raw user interactions into graph nodes and edges with specific attributes. Each node and edge is assigned parameters such as timestamps, action types, resource identifiers, and confidence scores. This parameter transformation allows the system to capture comprehensive activity context while managing complexity through standardized, queryable data attributes that can be efficiently stored and retrieved.
3Loss of information
If manual tracking of user activities is performed, then detailed information can be captured, but time consumption increases
Solution Approach 1:
The system implements self-service tracking by automatically capturing user actions and resources without requiring manual intervention. The monitoring module continuously observes user interactions with the electronic device, automatically logging actions (clicks, scrolls, selections) and associated resources (documents, websites, files). The activity context graph is automatically constructed and updated as users interact with the system, eliminating the need for manual data entry while capturing detailed activity information at scale.
Solution Approach 2:
The tracking system operates continuously in the background, maintaining an uninterrupted record of user activities across sessions and devices. The monitoring module runs persistently, capturing actions and resources as they occur without gaps. The activity context graph is continuously updated with new information, preserving the complete temporal sequence of user interactions. This continuous operation ensures detailed information capture without requiring periodic manual tracking interventions.
4Adaptability or versatility
If activity context graph is generated for each user, then personalized tracking is achieved, but data management complexity increases
Solution Approach 1:
The system segments the activity context graph by user, creating separate graph instances for each user while maintaining a unified data management approach. Each user's graph contains only their specific actions and resources, providing personalized tracking. The segmentation is implemented through user identifier fields in the graph nodes and edges, allowing the system to efficiently isolate and manage individual user data without requiring completely separate storage systems for each user.
Solution Approach 2:
The system merges the management of multiple user-specific activity context graphs into a single unified data management framework. The graph database infrastructure handles multiple user graphs simultaneously using common storage, indexing, and query mechanisms. User-specific graphs are combined in the underlying data structure through shared nodes and edges with user attribution, allowing efficient consolidation and management of all user data through a single system interface while maintaining the ability to extract and analyze individual user contexts.
Data Source
AI summary
A system and method for managing user activity context includes monitoring a user's actions on an electronic device; analyzing a resource accessed by the user; identifying an activity being performed by the user based on the analysis of the resource; and generating an activity context graph for the identified activity, wherein the activity context graph includes information regarding the resource. The activity context graph may be updated with additional resources accessed by the user if the additional resources are associated with the identified activity. The activity context graph may be provided to another user and may be updated to reflect the other user's profile, settings, or other information.