基于复杂网络的鼓浪屿旅游街区关联规则识别与特征分析

Identification and Feature of Association Rules of Tourist Blocks in Gulangyu Islet Based on Complex Network

基于复杂网络分析游客空间行为并挖掘旅游街区之间的关联特征,可以发现用地与功能之间显性和隐性的关联规则,精准识别旅游区用地空间结构,深入掌握旅游区发展现状,为智慧旅游与土地精细化转型提供支撑。本研究以世界文化遗产鼓浪屿为例,基于LBS大数据,使用复杂网络构建游客空间行为网络,利用关联规则分析重要节点的关联特征,进而使用用户画像数据,分析基于不同性别、年龄和客源地游客空间行为的街区关联规则。研究发现,“复杂网络+关联规则”算法可以挖掘游客随机行为中的隐藏规律,有效剖析旅游街区之间显性和隐性的关联规则。在游客空间行为轨迹网络中,各街区兼具“中心”与“枢纽”作用。既服务于本地游客又服务于外地游客的热门旅游街区表现出强关联规则。对外地游客具有较强吸引力的热门景点表现出较高的支持度,具有特色的旅游设施用地表现出较高的提升度。具有同质性的旅游街区之间关联性较强,人口特征差异对旅游街区关联规则影响显著。本研究可为城市更新背景下的旅游区用地整合、结构优化和游览线路调整提供决策参考,对于构建智慧旅游体系具有现实意义。

Spatial behavior reflects tourists' choice and preference for the land and function of tourist areas,which is very important for the management decision of tourist destinations.Based on the complex network analysis of tourists' spatial behavior and mining the correlation characteristics between tourist blocks,the explicit and implicit association rules between land use and function can be explored,the spatial structure of tourist areas can be accurately identified,and the development status of tourist areas can be deeply grasped,which provides support for smart tourism and fine land transformation.Taking Gulangyu Island,a world cultural heritage,as a case,this study extracts tourists' spatial behavior through location-based service big data,analyzes the characteristics of tourists' trajectory network by using complex network,explores the correlation characteristics between the internal land use of tourist areas based on tourists' spatial behavior by using association rule algorithm,and then analyzes the block association rules based on tourists' spatial behavior of different gender,age and source areas by using user portrait data.It is found that the algorithm of "complex network + association rules" can mine the hidden rules in tourists' random behavior and effectively analyze the explicit and implicit association rules between tourist blocks.In the trajectory network of tourists' spatial behavior,each block has both the functions of "center" and "hub".Popular tourist blocks that serve both local tourists and foreign tourists show strong association rules.Popular scenic spots with strong attraction to foreign tourists show high support,and the land for tourist facilities with characteristics shows high promotion.There is a strong correlation between homogeneous tourist blocks,and the difference of population characteristics has a significant impact on the association rules of tourist blocks.Theoretically,this study can enrich the cognition of tourism behavior,especially the relevance of land use caused by behavior,and construct association rules according to different demographic characteristics to supplement the demonstration of tourist demographic characteristics;In terms of methods,this study comprehensively uses complex network and association rule algorithm,which can more accurately fit the node and hierarchical structure of tourist behavior network,mine land association rules that are difficult to find by traditional methods,and provide new ideas for the coupling analysis of tourist behavior and tourist area land;In practice,based on the spatial behavior of tourists,the spatial structure of land use in tourist areas can be accurately identified,the development status of tourist areas can be more deeply grasped,the functional layout can be optimized,and the tourist facilities can be improved,thus providing support for smart tourism and fine land transformation.