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Sequence-Based Travel Route Recommendation Systems Using Deep Learning - A Case of Jeju Island -
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딥러닝을 이용한 시퀀스 기반의 여행경로 추천시스템 -제주도 사례-

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Type
Academic journal
Author
Journal
한국스마트미디어학회 스마트미디어저널 스마트미디어저널 제9권 제1호 KCI Accredited Journals
Published
2020.1
Pages
45 - 50 (6page)

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Sequence-Based Travel Route Recommendation Systems Using Deep Learning - A Case of Jeju Island -
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With the development of deep learning, studies using artificial neural networks based on deep learning in recommendation systems are being actively conducted. Especially, the recommendation system based on RNN (Recurrent Neural Network) shows good performance because it considers the sequential characteristics of data. This study proposes a travel route recommendation system using GRU(Gated Recurrent Unit) and Session-based Parallel Mini-batch which are RNN-based algorithm. This study improved the recommendation performance through an ensemble of top1 and bpr(Bayesian personalized ranking) error functions. In addition, it was confirmed that the RNN-based recommendation system considering the sequential characteristics in the data makes a recommendation reflecting the meaning of the travel destination inherent in the travel route.
#Deep learning #RNN #Recurrent Neural Network) #Recommendation systems #Jeju Island

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이정민 / 2018 / 지역분권화에 따른 지역관광 발전 방안 / 한국관광정책 (73):40~49 google schola B. Hidasi / 2015 / Session-based recommendations with recurrent neural networks / arXiv preprint arXiv : 1511. 06939 google schola 안병익 / 2016 / 다속성 태도 모델과 협업적 필터링 기반 장소 추천 연구 / 스마트미디어저널 5(2):84~89 dbpia 홍택은 / 2016 / 이미지와 텍스트 정보의 카테고리 분류에 의한 SNS 팔로잉 추천 방법 / 스마트미디어저널 5(3):54~61 dbpia Y. Zheng / 2009 / Mining interesting locations and travel sequences from GPS trajectories / Proceedings of the 18th international conference on World wideweb, ACM :791~800 google schola

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