Google llc (20240320420). PERSONALIZED AUTONOMOUS SPREADSHEETS simplified abstract
Contents
PERSONALIZED AUTONOMOUS SPREADSHEETS
Organization Name
Inventor(s)
Andrew J. Lavery of Austin TX (US)
Earl J. Wagner of Chicago IL (US)
Matthew Albright of Montclair NJ (US)
PERSONALIZED AUTONOMOUS SPREADSHEETS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240320420 titled 'PERSONALIZED AUTONOMOUS SPREADSHEETS
The method described in the abstract involves receiving a natural language query from a user requesting the creation of a personalized document with a tabular structure. The processing device then determines attribute categories for the document, identifies external data sources related to the user, retrieves data items from these sources, and populates the document with the retrieved data.
- The method involves creating personalized documents with tabular structures based on user queries.
- Attribute categories for the document are determined to organize the data effectively.
- External data sources, including subjective data sources related to the user, are identified and utilized.
- Data items indicative of the attribute categories are retrieved from the external sources.
- The personalized document is generated by populating each cell with the respective data item.
Potential Applications: - Personalized reports or summaries for individuals based on their data. - Customized tables or charts for users in various industries. - Automated document generation for personalized insights or recommendations.
Problems Solved: - Streamlining the process of creating personalized documents. - Enhancing the relevance and accuracy of data presented to users. - Improving efficiency in data retrieval and document generation.
Benefits: - Increased personalization and customization for users. - Time-saving through automated document creation. - Enhanced user experience with tailored information.
Commercial Applications: Title: Automated Personalized Document Generation for Enhanced User Insights This technology can be applied in industries such as finance, healthcare, marketing, and education for creating personalized reports, analytics, and recommendations tailored to individual users. The market implications include improved customer engagement, data-driven decision-making, and enhanced user satisfaction.
Prior Art: Readers can explore prior art related to document generation, data retrieval, and personalized content creation technologies to understand the evolution of similar concepts in the field.
Frequently Updated Research: Stay informed about advancements in natural language processing, data integration, and personalized content generation to leverage the latest technologies and methodologies for enhanced document creation processes.
Questions about Personalized Document Generation: 1. How does this method ensure data accuracy and relevance in the personalized documents? 2. What are the potential challenges in integrating multiple external data sources for document generation?
Original Abstract Submitted
a method includes receiving, by a processing device from a client device associated with a user, a natural language query corresponding to a request to create, for the user, a personalized document having a tabular structure, determining, by the processing device, one or more attribute categories pertaining to the personalized document, identifying, by the processing device, at least one external data source including at least one subjective data source related to the user, retrieving, by the processing device from the at least one external data source, data items indicative of the one or more attribute categories, and generating, by the processing device, the personalized document for the user by populating each cell of the personalized document with a respective data item.
