| CPC G09B 19/06 (2013.01) [G06F 18/22 (2023.01)] | 8 Claims |

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1. A word recommendation method in which a server recommends a word to a user, comprising:
a step of receiving training data from a network and training an AI model by using the training data;
a step of inputting (1) a user vector and (2) a word vector to the AI model, and generating (1) a user embedding vector and (2) a word embedding vector for determining whether the user knows a word related to the word vector, on the basis of the trained AI model;
a step of inputting (1) the user embedding vector and (2) the word embedding vector to a function for determining whether the user knows a word related to the word vector; and
a step of outputting a result value for predicting whether the user knows a word related to the word vector from the function,
wherein the AI model includes (1) the user embedding model for generating the user embedding vector, (2) the word embedding model for generating the word embedding vector of a word related to word information, and (3) the function, and
wherein the function is an arbitrary similarity scoring function for determining similarity between word embedding vectors acquired from the word embedding model.
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