GLORANG INC. (20240331811). METHOD AND SERVER FOR GENERATING, ON BASIS OF LANGUAGE MODEL, QUESTIONS OF PERSONALITY APTITUDE TEST BY USING QUESTION AND ANSWER NETWORK simplified abstract

From WikiPatents
Revision as of 16:12, 4 October 2024 by Wikipatents (talk | contribs) (Creating a new page)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

METHOD AND SERVER FOR GENERATING, ON BASIS OF LANGUAGE MODEL, QUESTIONS OF PERSONALITY APTITUDE TEST BY USING QUESTION AND ANSWER NETWORK

Organization Name

GLORANG INC.

Inventor(s)

Yong-hoon Kwon of Seoul (KR)

Sung-uk Choi of Seoul (KR)

Dong-jin Seo of Seoul (KR)

Tae-il Hwang of Seoul (KR)

METHOD AND SERVER FOR GENERATING, ON BASIS OF LANGUAGE MODEL, QUESTIONS OF PERSONALITY APTITUDE TEST BY USING QUESTION AND ANSWER NETWORK - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240331811 titled 'METHOD AND SERVER FOR GENERATING, ON BASIS OF LANGUAGE MODEL, QUESTIONS OF PERSONALITY APTITUDE TEST BY USING QUESTION AND ANSWER NETWORK

Simplified Explanation: This patent application discloses a method and server for generating questions for personality and aptitude tests using a question and answer network based on a language model. The server includes components such as a communication unit, a database for storing tester information, a memory for artificial intelligence model data, and a processor for generating question information.

Key Features and Innovation:

  • Method and server for generating questions for personality and aptitude tests.
  • Utilizes a question and answer network based on a language model.
  • Communication unit, database, memory, and processor components in the server.
  • Generates question information suitable for individual characteristics using artificial intelligence model data.

Potential Applications: This technology can be used in various personality and aptitude testing scenarios, such as recruitment processes, career counseling, and educational assessments.

Problems Solved: Addresses the need for personalized and relevant questions in personality and aptitude tests based on individual characteristics.

Benefits:

  • Provides tailored questions for personality and aptitude tests.
  • Enhances the accuracy and effectiveness of testing processes.
  • Improves the overall testing experience for individuals.

Commercial Applications: Title: "Personalized Personality and Aptitude Testing Technology" This technology can be commercially applied in recruitment agencies, educational institutions, career counseling centers, and online testing platforms. It can streamline the testing process, improve candidate assessment, and enhance user engagement.

Prior Art: Readers can explore prior art related to this technology by researching language models, artificial intelligence in testing, and question generation algorithms.

Frequently Updated Research: Stay updated on advancements in language models, artificial intelligence in testing, and personalized assessment technologies to understand the latest trends in this field.

Questions about Personality and Aptitude Testing Technology: 1. What are the key components of the server for generating questions in personality and aptitude tests? 2. How does the use of artificial intelligence models enhance the question generation process in personality and aptitude testing?


Original Abstract Submitted

a method and server for generating a question for personality and aptitude tests using a question and answer network based on a language model are disclosed. the server according to the present disclosure includes a communication unit configured to communicate with a terminal, a database configured to store tester information, a memory configured to store artificial intelligence model data for a generative artificial intelligence model, and a processor configured to generate personality and aptitude question information suitable for characteristics of a person from personal behavior characteristic information and existing question information by using the generative artificial intelligence model.