Abstract
Online forms in enterprise settings enable collection of information relevant to complex tasks such as putting together sales quotes. Form complexity can lead to errors, confusion, and/or delays as users that attempt to fill out the forms struggle to interpret the field meanings and navigate intricate processes. This disclosure describes techniques that build an understanding of forms using semantic and structural analysis, build contextual awareness based on profile data for entities completing a form and a dynamic knowledge base, and incorporate adaptive learning for error detection in forms. Techniques such as natural language processing, named entity recognition, question answering engines, summarization engines, etc. are used to build an artificial intelligence agent. Based on the form understanding, contextual awareness, and adaptive learning, the AI agent provides guidance to users entering data in forms. The techniques can be incorporated in any setting where complex forms are used. Implementation of the techniques can make it easier and faster for users to fill out forms, collaborate on enterprise tasks, and reduce the overall time to collect information via forms.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Metellus, Wicksell; Balireddi, Sindhura; Maelzer, Mike; Ganaba, Marim; and Shiroma, Erika, "Artificial Intelligence Agent for Contextual Guidance in Form Filling", Technical Disclosure Commons, (November 20, 2024)
https://www.tdcommons.org/dpubs_series/7575