Naver Corporation

Line Corporation

Jung Woo Ha

Dong Won Kim

Jeong Hee Kim

Chanju Kim

Jung Myung Kim

Hyuna Pyo

Jang Yeon Park

A method of determining a highlight section of a sound source includes obtaining a sound source and classification information of the sound source, and learning a neural network by using the sound source and the classification information. The neural network includes an input layer including a node corresponding to a feature value of each of a plurality of sections obtained by splitting the sound source according to a time axis, an output layer including a node corresponding to the classification information, a hidden layer defined between the input layer and the output layer, a first function between the input layer and the hidden layer, and a second function between the hidden layer and the output layer, wherein the first function includes an attention model for calculating a weighted sum of the feature value of each section. The highlight section of the sound source is determined based on weight information of a feature value node of each section included in the first function.

Data collecting method and system

Disclosed are a method and a system for automatically classifying data expressed as a plurality of factors with values of a text word and a symbol sequence by using deep learning. The method comprises the steps of: inputting the data expressed by the plurality of factors so as to express a word vector including sequence information of the factors through sequence learning of words corresponding to the factors with respect to each factor constituting the data in a first model; inputting an output of the first model so as to calculate points of each category for classifying the categories of the data by using the word vector including the sequence information of the factor in a second model; and determining at least one category for the data by using the points of each category.

Method and system for automatically classifying data expressed by a plurality of factors with values of text word and symbol sequence by using deep learning

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Seongnam-si, South Korea

Jung Woo Ha