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[학술저널]

  • 학술저널

조수현(고려대학교) 김보섭(고려대학교) 박민식(고려대학교) 이기창(고려대학교) 강필성(고려대학교)

UCI(KEPA) : I410-ECN-0101-2017-530-002130698

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초록

In order to attract foreign tourists, it is important to understand what factors on domestic tour spots are critically considered and how they are evaluated after visit. However, most of the researches on tour business have collected information from tourists through survey on a small number of tourists, which leads to inaccurate and biased conclusion. In this paper, we suggest a data-driven methodology to figure out tourists’ satisfaction factors and estimate sentiment scores on them. To do so, we collected review comments data from popular web site. Latent dirichlet allocation is employed to extract key factors and elastic net is used to estimate sentiment scores. Then, an aggregated evaluation score is generated by combining the factors and the sentiment scores per topics. Our proposed method can be used to recommend travel schedules with themes and discover new spots.

목차

1. 서론
2. 선행연구
3. 방법론
4. 실험설계
5. 실험 결과
6. 결론
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