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논문 기본 정보

자료유형
학술대회자료
저자정보
성다윗 (경희대학교) 문현실 (경희대학교) 김재경 (경희대학교)
저널정보
한국지능정보시스템학회 한국지능정보시스템학회 학술대회논문집 2016년 한국지능정보시스템학회 추계공동학술대회 논문집
발행연도
2016.11
수록면
58 - 64 (7page)

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초록· 키워드

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As the online marketing and tourism industry are closely related, many firms are taking advantage of online customer reviews as a new marketing tool. As one of the representative analysis methods for unstructured data, the text mining method has been actively developed and further extended into different analysis methods. The studies that use a text mining technique for analyzing the hotel industry have been extensively conducted; however, most of hotels have been conducting a survey in order to get the relevant data. Accordingly, this study aims to examine how customers assess particular aspects of a hotel based on either positive or negative opinions by analyzing customers’ review data. With the topic modeling which can account for the characteristics of a hotel review, this study seeks to recognize the distinguishing features of four representative hotels by using the extracted topics from topic modeling through decision tree classification. Hence, the newly found findings on the distinguishing factors of each hotel could contribute to the decision making processes regarding the marketing strategy in addition to development of hotels’ products as well as services. By realizing what customers think of their hotels, the managers along with marketing team could be benefitted from anticipating the future choices.

목차

〈초록〉
Ⅰ. Introduction
Ⅱ. Related Work
Ⅲ. Topic Modeling Based on Hotel Review Data
Ⅳ. Experimental Results
Ⅴ. Conclusion
Reference

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UCI(KEPA) : I410-ECN-0101-2018-020-000865773