Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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A Method for Short Text Classification using SNS Feature Information based on Markov Logic Networks

SNS 특징정보를 활용한 마르코프 논리 네트워크 기반의 단문 텍스트 분류 방법

  • Lee, Eunji (Dept. of Computer Engineering, Chosun University) ;
  • Kim, Pankoo (Dept. of Computer Engineering, Chosun University)
  • Received : 2017.03.15
  • Accepted : 2017.06.09
  • Published : 2017.07.31
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Abstract

As smart devices and social network services (SNSs) become increasingly pervasive, individuals produce large amounts of data in real time. Accordingly, studies on unstructured data analysis are actively being conducted to solve the resultant problem of information overload and to facilitate effective data processing. Many such studies are conducted for filtering inappropriate information. In this paper, a feature-weighting method considering SNS-message features is proposed for the classification of short text messages generated on SNSs, using Markov logic networks for category inference. The performance of the proposed method is verified through a comparison with an existing frequency-based classification methods.

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