Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Provided is a method of recommending a sticker through a dialogue 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 dialogue act analysis on the last utterance using a result of the surface analysis; extracting a dialogue context factor including a surface analysis result and a dialogue 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 dialogue context factor; and providing the selected sticker for the first user terminal.

Abstract: 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 dialogue 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 dialogue context factor; and providing the selected sticker for the first user terminal.

Abstract: Provided are a method and a computer program of recommending a responsive sticker. The method includes: generating dialogue 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 dialogue situation information database that is already collected and constructed, using the generated dialogue 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.

Abstract: 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.