Ncsoft Corporation

Kyeong Jong Lee

Taek Jin Kim

Jungsun Jang

Yeonsoo Lee

Jay June Lee

Sehee Chung

Provided is a method of recommending a sticker through an emotion analysis. The method of recommending a sticker through an emotion analysis, include: by a server, performing a surface analysis on the last utterance between the first user terminal and the second user terminal; performing an emotion analysis on the last utterance using a result of the surface analysis; extracting a dialog context factor including a surface analysis result and an emotion analysis result on a certain number of continuous utterances including the last utterance between the first user terminal and the second user terminal; selecting a sticker to be recommended to the first user using the dialog context factor; and providing the selected sticker for the first user terminal.

Methods and systems for analyzing communication situation based on emotion information

Provided is a method of determining the ranking of dialogue stickers based on situation and preference information. The method includes: analyzing utterances between the first user terminal and the second user terminal and selecting a sticker candidate group to be recommended to the first user terminal; calculating an expression suitability based on the preference and situation information in regard to the selected sticker candidate group; and determining the ranking of stickers in the order of suitability and then recommending a higher ranked sticker to the first user terminal.

Methods and systems for determining ranking of dialogue sticker based on situation and preference information

Provided is a method of recommending a dialogue sticker through similar situation retrieval. The method includes: generating dialogue situation information on the last utterances of the first user terminal and the second user terminal; retrieving a candidate situation having the most similar context from a dialogue situation information database, the situation including a plurality of continuous utterances; acquiring sticker information from pairs of utterance-sticker derived from the retrieved candidate situation and providing the sticker information for the first user terminal.

Methods and systems for recommending dialogue sticker based on similar situation detection

Provided is a method of recommending a sticker through a dialog act analysis. The method includes: by a server, performing a surface analysis on the last utterance between the first user terminal and the second user the terminal; performing a dialog act analysis on the last utterance using a result of the surface analysis; extracting a dialog context factor including a surface analysis result and a dialog act analysis result on a certain number of continuous utterances including the last utterance between the first user terminal and the second user terminal; selecting a sticker to be recommended to the first user using the dialog context factor; and providing the selected sticker for the first user terminal.

Methods and systems for analyzing communication situation based on dialogue act information

Provided are a method and a computer program of recommending a responsive sticker. The method includes: generating dialog situation information by analyzing pairs of the last utterance of a second user and previous utterances and previous utterances of a first user as an utterance of the second user terminal is inputted into the server; determining a similar situation from a dialog situation information database that is already collected and constructed, using the generated dialog situation information; determining whether it is a turn for the first user terminal to input a response; selecting a responsive sticker candidate group from the determined similar situation when it is a turn for the first user terminal to input the response; and providing information on at least one responsive sticker of the responsive sticker candidate group for the first user terminal.

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Yongin, South Korea

Kyeong Jong Lee