Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Structuring of Unstructured SNS Messages on Rail Services using Deep Learning Techniques

  • Park, JinGyu (Dept. of Computer Engineering, Hanbat National University) ;
  • Kim, HwaYeon (Dept. of Computer Engineering, Hanbat National University) ;
  • Kim, Hyoung-Geun (Smart R&D Center, U-CORE System Co.) ;
  • Ahn, Tae-Ki (Smart Station Research Team, Korea Railroad Research Institute) ;
  • Yi, Hyunbean (Dept. of Computer Engineering, Hanbat National University)
  • Received : 2018.06.22
  • Accepted : 2018.07.12
  • Published : 2018.07.31
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Abstract

This paper presents a structuring process of unstructured social network service (SNS) messages on rail services. We crawl messages about rail services posted on SNS and extract keywords indicating date and time, rail operating company, station name, direction, and rail service types from each message. Among them, the rail service types are classified by machine learning according to predefined rail service types, and the rest are extracted by regular expressions. Words are converted into vector representations using Word2Vec and a conventional Convolutional Neural Network (CNN) is used for training and classification. For performance measurement, our experimental results show a comparison with a TF-IDF and Support Vector Machine (SVM) approach. This structured information in the database and can be easily used for services for railway users.

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