특허 빅데이터 군집분석을 통한 항공보안 미래기술 예측
Prediction of Aviation Security Technologies through Cluster Analysis of Patent Big Data
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초록
항공 보안 기술은 미국의 9.11 테러를 기점으로 급격히 발전했지만 최근 발생한 지능적인 항공 테러로 인해 이를 해결하기 위한 진보된 항공 보안 기술 개발이 더욱 시급해졌다. 더욱 지능적으로 변해가는 범죄에 따른 위험을 감지하고 테러단체의 위협적인 행동으로부터 승객을 보호하고, 공항의정상적인 운영을 방해하는 불법 행위를 차단하기 위해 항공 보안 기술에 정보통신기술(information & communication technology, ICT)을 융합한 ‘ICT 융합 보안 기술’ 등 진보된 항공 보안 기술이 개발되고있다. 본 논문에서는 주요 국가의 항공 보안 기술개발에 대한 특허동향을 분석하여 기술 트렌드를 파악하였고, 텍스트마이닝 기법을 사용하여 특허를 군집화하고 주요 시장국의 부상 기술과 공백 기술을예측하였다. 또한 이에 대한 성능 평가를 진행하여 특허 군집화를 통한 예측 결과의 타당성을 확보하였다. 나아가 국제특허분류(international patent classification, IPC)코드의 빈도를 분석하고 연관규칙마이닝 기법을 사용하여 한국 특허에 대한 기술 연관성을 파악하였고, 이를 통해 국내 항공 보안 기술개발전략을 도출하였다.
Abstract
Aviation security technology has been emphasized than ever, since the 9.11 terror attacks in the United States. However, recent aviation terrors around the world made the urgent development of advanced aviation security technology inevitable. Information & communication technology(ICT) has recently been integrated to protect passengers from the threats by terrorist organizations and to prevent illegal activities that obstruct daily operations of airports. The development of advanced ICT-converged security technologies undergo to respond to various security concerns. In this paper, we analyze the trends in patents regarding aviation security technology from major countries and we predict the market’s emerging and non-existent technologies by using text mining techniques. In addition, we conduct a performance evaluation and acquire the validity of the prediction results through patent clustering. Furthermore, we analyze the frequency of IPC(international patent classification) codes and identify their relationships to Korean patents by using association rule mining techniques.
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