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Emotion Prediction of Paragraph using Big Data Analysis

빅데이터 분석을 이용한 문단 내의 감정 예측

  • Kim, Jin-su (College of Liberal Arts, Anyang University)
  • Received : 2016.09.30
  • Accepted : 2016.11.20
  • Published : 2016.11.28

Abstract

Creation and Sharing of information which is structured data as well as various unstructured data. makes progress actively through the spread of mobile. Recently, Big Data extracts the semantic information from SNS and data mining is one of the big data technique. Especially, the general emotion analysis that expresses the collective intelligence of the masses is utilized using large and a variety of materials. In this paper, we propose the emotion prediction system architecture which extracts the significant keywords from social network paragraphs using n-gram and Korean morphological analyzer, and predicts the emotion using SVM and these extracted emotion features. The proposed system showed 82.25% more improved recall rate in average than previous systems and it will help extract the semantic keyword using morphological analysis.

Keywords

Emotion Prediction;Korean Morphological Analyzer;Modified n-gram;Support Vector Machine(SVM);Association Rule;Sequential Pattern

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Cited by

  1. Associative Feature Information Extraction Using Text Mining from Health Big Data pp.1572-834X, 2018, https://doi.org/10.1007/s11277-018-5722-5