Cloud Software Group had 27 patents in future of work during Q4 2023. The Cloud Software Group Inc’s patents filed in Q4 2023 focus on task management processes, scheduling tasks based on participant availability, protecting shared screen content during screen sharing sessions, analyzing task information for project planning, and integrating messages with scheduled meetings for better organization. These patents aim to improve productivity and efficiency in task management and collaboration. GlobalData’s report on Cloud Software Group gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
Cloud Software Group grant share with future of work as a theme is 25% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Task management tool (Patent ID: US20230385731A1)
The patent filed by Cloud Software Group Inc. describes a task management process that involves receiving tasks from a service, computing task scores, determining user mood status, comparing mood status to task scores, recommending tasks based on the comparison, and sending the recommended task back to the service for user display. The method incorporates factors like task familiarity, task difficulty, user-selected mood status, and health data from smart devices to personalize task recommendations for users.
The patent also covers a computer program product and a system implementing the task management process. The program product includes instructions for receiving tasks, computing task scores, determining mood status, comparing scores to mood status, recommending tasks, and sending recommendations to the service. The system comprises storage and processors executing instructions to carry out the task management process, considering task familiarity, task difficulty, user mood status, and health data from smart devices. This innovative approach aims to enhance user productivity and task completion efficiency by leveraging mood status and other personalized factors in task recommendations.
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