18481910. Form Field Recommendation Management simplified abstract (Oracle International Corporation)
Contents
Form Field Recommendation Management
Organization Name
Oracle International Corporation
Inventor(s)
Subash Bhamidipati of Issaquah WA (US)
Kuldip Oberoi of Milpitas CA (US)
Karan Nayyar of Foster City CA (US)
John Ray Thomas of Aptos CA (US)
Blake Thomas Sullivan of San Francisco CA (US)
Raj Karpana Alagumalai of Redmond WA (US)
Van Hieu Tran of Pflugerville TX (US)
Form Field Recommendation Management - A simplified explanation of the abstract
This abstract first appeared for US patent application 18481910 titled 'Form Field Recommendation Management
The abstract describes a system that generates recommendations for form fields based on user interaction data with a digital form. The system compares the user interaction data with criteria obtained from data object resources to determine if recommendations should be allowed. If criteria are met, a machine learning model is applied to generate recommendations for form fields.
- System generates recommendations for form fields based on user interaction data
- Criteria obtained from data object resources determine if recommendations should be allowed
- Machine learning model is applied to generate recommendations for form fields
- Recommendations are based on user interaction with digital form
- System ensures recommendations meet specific criteria before being generated
Potential Applications: - Streamlining form completion processes - Enhancing user experience in digital forms - Improving data accuracy and completeness
Problems Solved: - Reducing manual effort in providing recommendations - Ensuring relevant recommendations are presented to users - Enhancing efficiency in form filling processes
Benefits: - Increased user satisfaction - Improved data quality - Time-saving in form completion
Commercial Applications: Title: Automated Form Field Recommendation System This technology can be utilized in various industries such as e-commerce, finance, and healthcare to optimize form filling processes, improve user experience, and enhance data accuracy. The market implications include increased efficiency, reduced errors, and improved customer satisfaction.
Questions about the technology: 1. How does the system determine when to generate recommendations for form fields? 2. What are the potential challenges in implementing this technology in different industries?
Original Abstract Submitted
Techniques for generating recommendations for form fields are disclosed. A system obtains user interaction data based on a user's interaction with a digital form. The digital form includes form fields mapped to attribute fields of data object resources. The data object resources specify criteria for when recommendations should be permitted or prohibited for the attribute fields of the business objects. The system obtains the criteria from the data object resources corresponding to the form fields in the digital form. The system compares the user interaction data with the recommendation enablement criteria to determine whether to allow the generation and presentation of recommendations for respective form fields. If the recommendation enablement criteria are met, the system applies a recommendation-type machine learning model to a set of input data including the user interaction data to generate a set of recommendations for a form field.
- Oracle International Corporation
- Subash Bhamidipati of Issaquah WA (US)
- Kuldip Oberoi of Milpitas CA (US)
- Karan Nayyar of Foster City CA (US)
- John Ray Thomas of Aptos CA (US)
- Blake Thomas Sullivan of San Francisco CA (US)
- Raj Karpana Alagumalai of Redmond WA (US)
- Van Hieu Tran of Pflugerville TX (US)
- Kevin Ng of Hampshire (GB)
- G06F9/451
- G06F40/174
- CPC G06F9/453