Electronics and Telecommunications Research Institute

Riiid Inc.

Fasoo Co., Ltd.

Jung Hyun Cho

Hag Young Kim

Yong Ju Lee

Byung Soo Kim

Chang Soo Kim

Seong Woon Kim

Dae Won Kim

Jae We Heo

Myeong Hoon Oh

Soo Cheol Oh

Sun Wook Kim

Ok Gee Min

Choon Seo Park

Yeong Min Cha

Young Duck Choi

Dong Min Shin

Jong Bae Moon

Joong Soo Lee

Song Woo Sok

Jin Eon Baek

Young Nam Lee

Byung Joo Lee

Hyun Bin Loh

Jin Hwan Lee

Jin Hwan Jeong

See Woo Lee

Jin Hwang Jeong

Jeong Moon Oh

Pil Jae Chae

Seo Yon Park

Chan Bae

The present disclosure relates to a system capable of increasing the accuracy of a prediction result when predicting a user drop-out rate or predicting a correct answer probability of a user in an online learning environment, and further relates to an operation method of the system. A system according to the present disclosure may include a plurality of encoder neural networks and a plurality of decoders, and may input question information to a kencoder neural network and input response information to kdecoder neural network to learn the system, thereby predicting the user drop-out rate information and the users correct answer probability information with higher accuracy on the basis of the learned system.

System for predicting user drop-out rate and tracking user knowledge based on artificial intelligence learning and method therefor

According to an embodiment of the present disclosure, a pre-training modeling system for predicting an educational element using a pre-trained AI model includes: a pre-training unit configured to pre-train an AI model, through an evaluation element that can be automatically collected every time a user solves an individual question by receiving an interaction element according to an offline user's operation from a user terminal, classifying an AI element of educational content into the interaction element and the educational element, and intersecting the interaction element and the educational element; a fine-tuning unit configured to perform an additional training operation with respect to the pre-trained AI model, according to an educational element to be predicted; and an educational element prediction unit configured to predict, on the basis of the fine-tuned AI model, one or more pieces of information among test scores, grades, qualifications, and review information indicating whether the user got a correct answer when re-solving the same question, which are information that must be separately input from the user because the amount of information automatically collected every time the user solves an individual question is small or cannot be automatically collected.

Pre-training modeling system and method for predicting educational element

The present disclosure provides a virtual file management method and apparatus, and a computer-readable recording medium thereof, which may comprises obtaining an object identifier for distinguishing objects, wherein the object includes at least one of a virtual file or a virtual folder and obtaining the object based on the obtained object identifier.

Method for managing virtual file, apparatus for the same, computer program for the same, and recording medium storing computer program thereof

Disclosed is a virtual desktop service method. The virtual desktop service method includes configuring and measuring users and resources according to predetermined criteria, copying operating system files and data files to be provided to the users before use request, receiving request to use a virtual machine from any one of the users and performing user authentication and work approval, and providing an operating system file and a data file of the any one of the users, among the copied operating system files and data files, to the any one of the users according to the use request to transmit a virtual desktop environment. Consequently, the virtual desktop service method performs a service to provide a virtual machine to a user in real time.

Virtual desktop service apparatus and method

Provided is a virtual desktop service, and disclosed is a system for providing a server virtual machine, including: a client configured to receive allocation of a virtual machine for using a virtual desktop service; a connection broker configured to control a type of virtual machine to be allocated to be classified according to user terminal registration information of the client, any one operation server to be selected among a plurality of operation servers, and the virtual machine to be allocated; the plurality of operation servers configured to provide the client with a virtual machine under a control of the connection broker; and a shared storage configured to store data related to the client for providing the virtual machine, and provide the stored data to the operation servers, a method of providing a server virtual machine, and a server device supporting the same.

Method and system for providing server virtual machine for real-time virtual desktop service, and server device supporting the same

Disclosed is a dynamic load balancing system. The dynamic load balancing system includes a resource management master managing bare servers that do not execute services and having a hierarchical structure and a service master dynamically allocating the bare servers to a load balancing server or a service execution server or dynamically releasing the pre-allocated load balancing server or service execution server by the bare servers, in consideration of monitoring information on a state or performance of a server and service requirements to be provided.

Dynamic load balancing system and method thereof

Provided are a method and apparatus for obtaining a minimum cost vector for making a skyline object in a multi-dimensional space. The method includes calculating respective vector values having a query point and respective moving points to which the query point is moved as both end points in a multi-dimensional space having a plurality of coordinate axes, and selecting a vector value whose moving point is included in a skyline and has the minimum distance value from the query point as the minimum vector value from among the vector values.

Method and apparatus for obtaining minimum cost vector for making skyline object in multi-dimensional space

Growing community of inventors

Seoul, South Korea

Jung Hyun Cho