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Method for Dynamically Translating Technical Content Based on User Feedback

IP.com Disclosure Number: IPCOM000248033D
Publication Date: 2016-Oct-19
Document File: 5 page(s) / 211K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method for translating content based on user feedback according to the user's understanding, which may change based on knowledge gained by the user during the session is disclosed.

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Method for Dynamically Translating Technical Content Based on User Feedback

Disclosed is a method for translating content based on user feedback according to the user's understanding, which may change based on knowledge gained by the user during the session.

Businesses strive to represent their domain specific knowledge in forms that allow this information to be queried to solve problems efficiently. The objective is typically to promote information management, often with the goal of saving time and money. Today, the domain specific knowledge is usually stored in dictionaries, wikis, or more popularly identified as ontologies. Data model are typically used to represent represent an ontology as knowledge base classifying a set of concepts within a domain and the relationships between these concepts. Understanding ontologies for domains such as engineering requires the use of very complex concepts and technical jargon that are difficult to define for non-expert users. This makes any concept contained within the ontology difficult to communicate to non-expert users, such as students or business professionals, who have not yet attained the concept's requisite level of expertise. Translation from the ontology queried to terms that the user can understand is then required for allowing all to learn from the knowledge as desired. Complicating this effort, each individual may understand different subsets and domains of a single ontology to varying degrees based on overall level of education. The often wildly different starting points of users can strongly impact efforts to translate between knowledge bases and stymie efforts to improve productivity. If a translation fails to clarify information for the user due to an incorrect assumption about starting points, then the translation itself hinders swift learning.

This disclosure is a unification of these concepts for a more robust system that is capable of incorporating user specific information into the translation process. The objective is to enable the flexible translation of concepts between two domains, as tailored to the user. Furthermore, this complete system would enable a tool that is capable of presenting information to the user in a way that evolves as they do. As the user increases their starting knowledge, the translations increase in complexity to match the user's understanding; this allows the user to maximize their time absorbing newer and more applicable ideas.

Features may include:
Customizing an ontology to multiple users, broken down by predefined generic classes.

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In one embodiment the abstract system described above could be implemented as part of a customized document/report/information extraction tool used to answer questions for the user. The steps as envisioned for this article are listed below. The general flow is shown in Figure 2.

Example scenario for the medical field:

User enters program for first time and registers an account.

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Providing traini...