Author-Created Digital Agents for Document Content Corpora
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Solution Overview
Problem
Users of electronic documents often face challenges in interpreting content without immediate access to the author, leading to inefficient searches for additional information, as existing technologies do not provide a seamless way to interact with the author or access relevant information directly within the document.
Innovation Solution
Author-created digital agents and content corpora that allow users to interact with a virtual author or interfaces, using hybrid intelligence to search and provide relevant information from curated content associated with the document, reducing the need for external searches and minimizing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the author is made physically present or immediately accessible to answer questions, then the consumer can obtain clarifications, but the document simplicity and user experience are degraded
Solution Approach 1:
The patent introduces a chatbot as an intermediary between the document consumer and the author. The chatbot is trained on the document content and can answer consumer questions without requiring the author's physical presence. This mediator resolves the contradiction by providing information access while preserving document simplicity.
Solution Approach 2:
The chatbot enables self-service by allowing consumers to obtain information and clarifications autonomously through automated interactions. The system serves itself by using the document content to train the chatbot, which then independently answers questions without human intervention, resolving the contradiction between information accessibility and maintaining simple document delivery.
2Loss of information
If the consumer searches for information from online resources or contacts the author, then additional information can be obtained, but time and resources are consumed
Solution Approach 1:
The chatbot is pre-trained on the document content before any consumer interactions occur. This preliminary action of training the model on the document allows it to immediately answer questions without requiring consumers to perform external searches or wait for author responses, thus resolving the contradiction between information completeness and time consumption.
Solution Approach 2:
The chatbot serves as an intermediary that provides immediate access to document-related information. Instead of consumers needing to search online resources or contact authors, the chatbot mediates by providing instant answers based on its training data, eliminating time loss while maintaining information completeness.
3Ease of operation
If a virtual author interface is implemented to provide information, then user experience is enhanced, but resource consumption increases
Solution Approach 1:
The chatbot implements self-service by using the document content itself to train the model. The system serves itself by converting the document into training data, which then enables autonomous question-answering capabilities. This approach enhances user experience through an interactive virtual author while minimizing additional resource consumption by reusing existing document content.
Solution Approach 2:
The patent changes the parameter of information representation by converting static document content into a trained chatbot model. This parameter change from static text to an interactive AI agent enhances user experience while the model's efficiency optimizes resource consumption during runtime interactions.
Data Source
AI summary
Author-created digital agents and content corpora for electronic documents are described. A content corpora service can include application programming interfaces such as for adding content to a corpus, attaching a corpus to a document, retrieving corpora associated with an author, and searching content of a corpus. An author-created digital agent can receive a request from a consumer of a document, determine corpora associated with the document, formulate a query based on the request, and search content associated with the corpora associated with the document.