Method of recommending preceding educational content and educational content recommendation device for recommending preceding educational content
AssigneeRiiid Inc.
InventorHyun Bin LOH
Life of this patent
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Abstract
Provided are a method of recommending preceding educational content and an educational content recommendation device for recommending preceding educational content. The method includes acquiring a language model of which training has been completed, updating the language model by tuning the language model to acquire a target language model, and determining preceding educational content through the target language model. The acquirement of the target language model includes acquiring an educational data set including first clustering data and second clustering data and updating the language model to predict a probability that the first clustering data is a next token of the second clustering data.
Claims9
A method of recommending preceding educational content by an educational content recommendation device for acquiring educational content and recommending preceding educational content required for solving the educational content, the method comprising:
- acquiring a language model of which training has been completed;
- updating the language model by tuning the language model to acquire a target language model;
- and
- determining preceding educational content through the target language model,
- wherein the acquirement of the target language model comprises:
- acquiring an educational data set including first clustering data and second clustering data;
- and
- updating the language model to predict a probability that the first clustering data is a next token of the second clustering data.
An educational content recommendation device for acquiring educational content and recommending preceding educational content required for solving the educational content, the educational content recommendation device comprising:
- a transceiver configured to communicate with a user terminal;
- and
- a controller configured to acquire target educational content through the transceiver and determine preceding educational content required for solving the target educational content,
- wherein the controller acquires a language model of which training has been completed, updates the language model by tuning the language model to acquire a target language model, and determines preceding educational content through the target language model, and
- wherein the controller acquires an educational data set including first clustering data and second clustering data and acquires the target language model by updating the language model to predict a probability that the first clustering data is a next token of the second clustering data.
Dependencies are inferred from the claim text.