US20260023471
2026-01-22
Physics
G06F3/04845
The disclosed method involves creating a journal using a personal knowledge graph derived from user data with established relationships. The journal is visually represented on a display screen, featuring an image and accompanying text. The image is generated from the user's data, and users can modify the image through input, which in turn alters the journal's text. This approach leverages personal knowledge graphs to enhance the journaling experience by integrating user-specific data.
Artificial intelligence (AI) technologies have become prevalent across various industries, enhancing competitiveness and efficiency. Knowledge graphs, a type of knowledge base, are utilized for improving AI model performance by providing structured data. There's a growing trend towards on-device AI, where user devices independently collect and process data, reducing reliance on external servers. This shift supports more personalized and autonomous applications, such as the proposed journaling method.
The method's core functionality includes generating a journal through a personal knowledge graph, displaying relevant images and text, and allowing user interaction to modify these components. The changes made to the images directly influence the journal's text, creating a dynamic and interactive user experience. This adaptability is facilitated by a user device equipped with memory, processors, and an input/output interface, executing instructions to manage the journal's content and presentation.
The method is executed by a user device, which processes the knowledge graph and manages user interactions to modify journal entries effectively.
This method offers a personalized journaling solution that adapitates to user data, providing a more intuitive and engaging experience. It can be particularly beneficial for users seeking a reflective and customizable journaling tool. By leveraging on-device AI, the method ensures privacy and efficiency, reducing the need for external data processing. This approach aligns with the broader trend of enhancing user autonomy and personalization in digital applications.