Box had five patents in future of work during Q1 2024. Box Inc has filed patents for content management systems that automatically determine activity-based content object access permissions and make recommendations. These systems utilize machine learning models formed from user interactions to continually update access permissions for collaborative relationships. Additionally, scalable architectures are provided for generating jobs by applying user-specified rules to events in an action log framework stream within collaboration environments. The patents also cover methods for managing shared content objects across interconnected computer systems, selecting workflows based on event attributes, and executing operations over shared content objects. GlobalData’s report on Box gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Box grant share with future of work as a theme is 40% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Activity-based content object access permissions (Patent ID: US20240037266A1)
The patent filed by Box Inc. describes methods, systems, and computer program products for content management systems that automatically determine activity-based content object access permissions and make recommendations for such permissions. A machine learning model is created from user interactions with content objects, continually updated based on ongoing observations, and used to assign access permissions to collaborative relationships between users. These permissions can be automatically assigned or presented as recommendations to the invitor, who can accept or reject them. The system generates training datasets, feature structures, and interaction event groups to train the model and validate its performance, ensuring that access roles and permissions are assigned accurately based on user interactions and new attributes of the collaborative relationship.
The method, computer-readable medium, and system outlined in the patent focus on leveraging machine learning models to automate the assignment of access permissions in collaborative relationships within content management systems. By analyzing user interactions with content objects and forming training datasets based on these interactions, the system can accurately assign access roles and permissions to invitees collaborating on specific content objects. The use of feature structures, interaction event groups, and collaboration network data structures enhances the accuracy of these assignments, ensuring that the recommendations or automatic assignments are based on a thorough analysis of user behavior and relationship attributes. Overall, the patent outlines a comprehensive approach to optimizing content object access permissions in collaborative environments through the use of machine learning and data-driven techniques.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
