한국ITS학회 논문지 (The Journal of The Korea Institute of Intelligent Transport Systems)

  • 제15권1호
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  • Pages.109-118
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  • 2016
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  • 1738-0774(pISSN)
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  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
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교통망 관찰과 도시 특징지도를 위한 퍼지영역 온톨로지 기반 오피니언 마이닝

Fuzzy Domain Ontology-based Opinion Mining for Transportation Network Monitoring and City Features Map

  • 투고 : 2015.12.04
  • 심사 : 2016.02.03
  • 발행 : 2016.02.28
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초록

트래픽 혼잡이 도심지역에서는 급속히 증가하고 있다. 이 문제를 해결하기 위하여 유용한 핵심 정보를 사용하여 트래픽 상황을 신속하게 인지할 수 있는 실시간 그리고 지능적인 방안이 필요하다. 본 연구는 실시간 교통망을 관찰하고 여행자를 위한 도시의 극성 지도를 구축하기 위하여 퍼지기반 오피니언 마이닝 시스템을 제안한다. 제안된 시스템은 도시의 교통 상황에 관련한 트위터 및 리뷰를 추출하고, 특징 오피니언을 추출하여, 퍼지기반 오피니언 마이닝 시스템를 사용하여 교통 및 도시의 특징적 극성을 규명한다. $Prot{\acute{e}}g{\acute{e}}$ OWL 과 자바를 사용하여 퍼지기반 오피니언 마이닝 시스템과 그 지능형 프로토타입을 개발한다. 실험을 통하여 트위트 및 리뷰의 분석과 오피니언 마이닝 측면에서 성능이 개선됨을 확인하였다.

Traffic congestions are rapidly increasing in urban areas. In order to reduce these problems, it needs real-time data and intelligent techniques to quickly identify traffic activities with useful information. This paper proposes a Fuzzy Domain Ontology(FDO)-based opinion mining system to monitor the transportation network in real-time as well to make a city polarity map for travelers. The proposed system retrieves tweets and reviews related to transportation activities and a city. The feature opinions are extracted from these tweets and reviews and then used FDO to identify transportation and city features polarity. This FDO and intelligent prototype are developed using $Prot{\acute{e}}g{\acute{e}}$ OWL (Web Ontology Language) and JAVA, respectively. The experimental result shows satisfactory improvement in tweets and review's analyzing and opinion mining.

키워드

참고문헌

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피인용 문헌

  1. Graph Adaptation Network with Domain-Specific Word Alignment for Cross-Domain Relation Extraction vol.20, pp.24, 2016, https://doi.org/10.3390/s20247180