大數據於風景景點之容留量相關管理之研究－以桃園市景點為研究對象;Research on the management of big data in the capacity of scenic spots - taking Taoyuan City scenic spots as the research object

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题名:	大數據於風景景點之容留量相關管理之研究－以桃園市景點為研究對象;Research on the management of big data in the capacity of scenic spots - taking Taoyuan City scenic spots as the research object
作者:	陳俊良;Chen, Chun-Liang
贡献者:	企業管理學系在職專班
关键词:	行動信令資料;景點人次;容留量;人潮示警燈號;即時影像;cellular probe data;Visitor times;capacity;crowd warning lights;real-time images
日期:	2022-07-21
上传时间:	2022-10-04 11:09:53 (UTC+8)
出版者:	國立中央大學
摘要:	本研究乃以桃園市觀光景點發布人數燈號為背景，研究經由大數據資料探勘方法，以行動通訊去識別化的技術，以便收集統計並分析出適用的資訊，轉化成為提供主管機關和提供給民眾運用的個案研究分析。以期能達成下列2個重要目的：大數據資料探勘實務方面，本研究蒐集並整理桃園市景點資訊的實際運作，探討相關資訊演進與改善，藉由比對台灣其他中央和縣市機關的發布資料優缺點的分析，提供未來其他類似方案規劃時，能更有效地達成資料探勘的最佳化。藉由個案研究過程實證，內部先以大數據特徵全面、準確且即時收集資料，外部再依實務調整成紅黃綠三色區分的人潮警示燈號做運用，另外再增加景點即時影像輔助。比對類似案例分析，找出可具仿傚的關鍵因素，做為台灣未來智慧觀光服務轉型計畫內重要實務數據運用和整合進入未來發展。主要景點管理在於場地場館主管機關長期收集累積資訊，搭配前線交通疏導的交通管制人員或交通警察單位、甚至道路相關規畫的交通單位都應該一起納入，作為實測的合作單位，並且依據實測的校正之後，讓整個數據的信度、效度提高，回饋以作為後續的更優化是合現地的推估，也因推估應用更便利，能將開放資料推估應用在更多的關係人、機關和參與者。;This research is based on the background of the number of people issued by the tourist attractions in Taoyuan City and researches the technology of de-identification of mobile communication through big data data mining method, to collect statistics and analyze the applicable information and transform it into the information provided to the competent authority and the Case study analysis of popular use. To achieve the following two important purposes: In terms of big data mining practice, this study collects and organizes the actual operation of Taoyuan City′s scenic spot information, explores the evolution and improvement of related information, and compares the data released by other central, county and city agencies in Taiwan. The analysis of shortcomings can more effectively achieve the optimization of data mining when providing other similar program planning in the future. Based on the empirical evidence of the case study process, the internal data is collected comprehensively, accurately, and in real-time with the characteristics of big data, and the external traffic warning lights are adjusted to red, yellow, and green according to the actual situation. In addition, real-time image assistance of scenic spots is added. Comparing similar case studies, find out the key factors that can be imitated, and use and integrate them into future development as important practical data in Taiwan′s future smart tourism service transformation plan. The main attraction management lies in the long-term collection of accumulated information by the competent authorities of venues and venues. Traffic control personnel or traffic police units with front-line traffic guidance, and even traffic units related to road planning should be included together as a cooperative unit in the actual measurement, and corrections based on the actual measurement should be included. After that, improving the reliability and validity of the entire data and giving feedback as follow-up optimization is a suitable estimate, and because the estimate application is more convenient, the open data estimate can be applied to more stakeholders and institutions. and participants.
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