arXiv 1811.034262018-11-05cs.CY

基于位置社会网络（LBSN）的旅游者序列活动模式研究

A Study of Tourist Sequential Activity Patterns through Location Based Social Network (LBSN)

Anmoila Talpur, Yanchun Zhang

备注：: Research Questions 1.What are the most common tourist sequential activity patterns in Singapore? 2.What are the effective methods of sequential activity analysis using the LBSN data in Singapore? 3.What are the most interesting insights resulting from the tourist sequential activity pattern analysis in Singapore?

摘要：

序列模式挖掘是建立模式和挖掘某些活动趋势的重要组成部分。深入了解游客流动和活动模式被认为在许多方面对旅游部门有益，例如为游客设计更好的旅游套餐，最大限度地提高游客活动参与度和满足游客需求。本研究建议采用移动社交媒体数据，有效地捕捉在新加坡的旅游活动信息，并利用先进的数据采掘技术，提取有价值的见解，游客的行为。本研究所提出的方法和研究结果有可能支持旅游管理者和决策者在旅游目的地管理中做出更好的决策。

英文摘要：

Sequential Pattern Mining is an important component in establishing patterns and mining trends of certain activities. Insights into tourist movement and activity patterns is deemed beneficial for the tourism sector in many ways, such as designing better travel packages for tourists, maximizing the tourist activity participation and meeting the tourist demands. This research proposes to adopt mobile social media data for effective capturing of tourist activity information in Singapore and utilizes advanced data mining techniques for extracting valuable insights into tourist behavior. The proposed methods and findings of the study have the potential to support tourism managers and policy makers in making better decisions in tourism destination management.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。