Methods and systems for analyzing communication situation based on emotion information

• US 9,792,279 B2
• Filed: 07/14/2015
• Issued: 10/17/2017
• Est. Priority Date: 01/19/2015
• Status: Active Grant

• Current Assignee: NCSoft Corporation
• Original Assignee: NCSoft Corporation
• Inventors: Kim, Taek Jin, Lee, Jay June, Jang, Jungsun, Chung, Sehee, Lee, Kyeong Jong, Lee, Yeonsoo
• Primary Examiner(s): ADESANYA, OLUJIMI A
• Application Number:
  US14/799,545
• Publication Number:
  US 20160210279A1
• Time in Patent Office: 826 Days
• Field of Search: 704 9
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation

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.

Claims

1. A method of recommending a dialogue sticker group by use of a server that is connected to a database, a first user terminal and a second user terminal through a network and relays an utterance inputted to a messenger between the first user terminal and the second user terminal, the utterance including at least one of a text and an image, the method comprising:

causing the server to analyze utterances, generate utterance data from the analyzed utterances and store the utterance data in the database, the utterance data comprising dialogue situation information, the dialogue situation information including information on dialogue act category, information on emotion category, information on emotion strength of a user, and one or more keywords extracted from the utterances;

analyzing a set of continuous utterances between the first and second user terminals to determine a dialogue situation between the first and second user terminals, the set of continuous utterances including at least one utterance from the first user terminal and at least one utterance from the second user terminal;

retrieving, from the utterance data, a portion of the dialog situation information, wherein the portion has a dialog situation similar to the dialog situation between the first and second user terminals;

determining a relationship between a first user of the first user terminal and a second user of the second user terminal from a set of continuous utterances between the first user terminal and the second user terminal;

selecting a sticker group based on the retrieved portion of the dialog situation information and the determined relationship, the sticker group including one or more stickers; and

recommending the selected sticker group on a display device of the first user terminal.

2. A non-transitory computer readable medium storing one or more sequences of pattern data for recommending a dialogue sticker group by use of a server that is connected to a database, a first user terminal and a second user terminal through a network and relays an utterance inputted to a messenger between the first user terminal and the second user terminal, the utterance including at least one of a text and an image, wherein execution of the one or more sequences of the pattern data by one or more processors causes the one or more processors to perform the steps of:

causing the server to analyze utterances, generate utterance data from the analyzed utterances and store the utterance data in the database, the utterance data comprising dialogue situation information, the dialogue situation information including information on dialogue act category, information on emotion category, information on emotion strength of a user, and one or more keywords extracted from the utterances;

analyzing a set of continuous utterances between the first and second user terminals to determine a dialogue situation between the first and second user terminals, the set of continuous utterances including at least one utterance from the first user terminal and at least one utterance from the second user terminal;

retrieving, from the utterance data, a portion of the dialog situation information, wherein the portion has a dialog situation similar to the dialog situation between the first and second user terminals;

determining a relationship between a first user of the first user terminal and a second user of the second user terminal from a set of continuous utterances between the first user terminal and the second user terminal;

selecting a sticker group based on the retrieved portion of the dialog situation information and the determined relationship, the sticker group including one or more stickers; and

recommending the selected sticker group on a display device of the first user terminal.