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地圖 : 中華民國地圖學會會刊

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篇名 Web2.0網路服務的資料探勘—以國家風景區的旅客滿意度調查為例
卷期 23:2
並列篇名 Data Mining in Web2.0 Geotagged Photos — An Example of Hot Spots Recreational Satisfaction in National Scenic Areas
作者 林祥偉
頁次 001-017
關鍵字 坐標資訊標籤相片遊憩景點滿意度資料探勘國家級風景特定區Geotagged PhotosRecreational SatisfactionData MiningNational Scenic Area
出刊日期 201310

中文摘要

本研究以Flickr相片分享服務為資料探勘對象,以景點上傳相片密度,作為遊客對遊憩景點滿意度的評估依據。並在實證的案例中,以台灣地區13個國家級風景特定區為範圍,透過比對呈現出不同遊客多元觀點的網路上傳相片密度,與交通部觀光局,針對遊客意象問卷做成的滿意度評比,在剔除景點上傳相片密度受到道路、海岸線、或都會地區等易達性因素影響最大的兩個國家風景區後,發現兩者的排名,呈現一致性極高的結果。此外,由於國家風景區的範圍大小不一,且景點數目不同,因此更進一步針對每個國家風景區內各鄉鎮的旅遊景點,應用景點平均照片密度指標,進行滿意度的評比,以求更能貼近遊客真實遊憩體驗,提供尚未到過該地區遊客更全面的參考資訊。

英文摘要

This study uses the database of the Flickr photo sharing service, and web2.0 websites as data mining subjects to mine the photo locations of all photos located in Taiwan as a basis for evaluating recreational satisfaction of tourists toward these spots. This study further uses the 13 national scenic areas as the range to evaluate the density of photos of each scenic spot in the range, and the satisfaction evaluations for tourists´ images by the Tourism Bureau. After discarding national scenic areas that are densely distributed over areas with convenient transportation, such as roads, coastlines, or urban areas; areas with higher accessibility evidently determine the density of internet upload photos in terms of spatial distribution. The results indicate a high degree of consistency with real-world satisfaction evaluations. The results also show that the different boundary of national scenic areas and the number of scenic spots influence the satisfaction ranking results. Therefore, this study extends application of data mining photo density indicator to evaluation satisfaction of each scenic spot in townships and villages in each national scenic area. Thus, the comparisons of tourist areas within each national scenic area by village or township would be closer to the real leisure experiences of tourists, as compared to the average satisfaction for national scenic areas, and would have greater general referential value.

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