基于网页旅游攻略的旅行线路规划

为帮助旅行者规划旅行线路,以旅游攻略为数据源,针对旅行线路规划问题中可选景点的动态性问题,根据传统车辆路径问题求解方法中两阶段法的先分组再定路线的策略,重点研究并设计改进了一种基于攻略中景点出现频率的先分组再定路线的启发式旅行线路规划策略用于自动规划旅游行程。试验结果表明,使用本文所提出的方法生成的旅游线路,时间分配更加合理,游览的景点间路程更短,线路的游览时间与景点间距离的费效比更高,对于游客规划旅行线路有着很大的现实意义。     

基于多源数据的梅州市旅游资源综合评价分析

旅游大数据对旅游者的行为模式的影响日趋明显,在分析研究区旅游资源现状基础上,利用传统数据和网络数据,选取4个一级因子和8个分级指标,构建梅州市旅游资源综合评价体系,对梅州市旅游资源进行综合评价分析。结果表明梅州市旅游资源北密南疏,具有从城市中心向各县市递减的趋势,其中218个旅游点综合评价得分在0~0.7之间,集中分布在0.1~0.2间,自然类的旅游资源高分的景点所占比重最多。基于评价得分核密度分析的旅游资源也具有空间差异性,自然类景观的综合评价得分呈多格局分布特性,人文类和休闲类的旅游资源综合评价得分的空间格局为单一中心格局。梅州市旅游资源及其评价得分具有空间分异特征,建议各类景点发挥协同组团的优势,优化旅游资源发展空间格局,将梅州市建造成世界客家文化旅游休闲目的地,并对同类型城市旅游资源发展规划提供借鉴。     

移动轨迹聚类方法研究综述

轨迹数据是人类移动行为的表征,能够映射出人的出行模式和社会属性等信息。怎样有效挖掘轨迹数据蕴藏的人类活动规律一直是研究的热点。通过轨迹聚类发现行为相似的类簇,从而探究群体的移动模式是轨迹挖掘和深度应用常见的方法之一。本文首先根据轨迹数据的特点,将轨迹数据模型分为轨迹点模型和轨迹段模型,并据此定义相应的相似性度量：空间相似性度量和时空相似性度量;然后,对两类模型的聚类方法进行了综述,并总结不同聚类算法的优缺点,以期为不同应用选取聚类算法提供科学依据;最后对移动轨迹数据聚类方法研究的发展趋势进行了讨论。     

基于地理量化方法的四川省A级旅游景区空间分布结构研究

利用数理统计和地理信息空间分析方法,从定量和定性两方面探讨四川省221个A级旅游景区的空间分布结构,分析其空间分布规律。结果表明：四川省A级旅游景区的空间分布类型属于集聚型,且区域间差异较大,空间分布均匀度较低,不均衡性显著;四川省A级旅游景区规模等级结构表现为中间大两头小的纺锤形结构,中端的市场供给占据上风;四川省A级旅游景区空间分布受地理区位、交通条件、景区地域组合状况和经济发展水平等多种因素综合影响。     

基于网络文本迁移学习的旅游知识图谱构建

在线旅游服务模式和海量网络文本的出现为旅游产业规划和用户出游推荐提供了新的信息支撑。然而实时更新的网络文本语义模糊、信噪比低,难以利用,由此,提出了一种基于领域本体和迁移学习的旅游知识图谱构建方法。首先,基于行业规范定义了旅游景点特征体系,建立了以旅游景点为核心的旅游知识图谱,支持景点语义特征的全方位刻画;然后,通过迁移学习方法将预训练语言模型改造为定制化知识抽取器,从网络文本中获取知识三元组,并融合游客足迹、兴趣点语义等信息将分散的相关信息整合为系统性的旅游景点知识图谱。知识抽取实验结果表明,相较于常用的LDA（latent Dirichlet allocation）模型,定制化知识抽取器获取的景点语义知识,其精度与完整性分别提升了50.7%和670%。所构建的旅游景点知识图谱可全面表达现实中的旅游场景,支撑不同尺度下游客行为与市场需求的深入解析,为旅游目的地可持续发展规划提供决策支持。     

出租车轨迹数据的南京人群出行模式挖掘

针对现有出租车轨迹数据挖掘中时间序列邻近度量方法存在的问题,提出一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,进而研究城市人群出行行为的时空差异。以南京市为例,结合电子地图对出行模式的空间分布特征进行分析,证明了本文所提出的方法的有效性。实验结果表明:在空间分布上,工作日出租车出行模式按照平均出行频次由高到低排序,从城市中心向四周扩散,呈中心环状分布,出行模式区域界限较为明显,同类出行模式分布区域对应相似的功能。提出了一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,有效地分析城市人群出行行为的时空差异。     

Latent spatio-temporal activity structures: a new approach to inferring intra-urban functional regions via social media check-in data

Abstract

This article introduces a novel low rank approximation (LRA)-based model to detect the functional regions with the data from about 15 million social media check-in records during a year-long period in Shanghai, China. We identified a series of latent structures, named latent spatio-temporal activity structures. While interpreting these structures, we can obtain a series of underlying associations between the spatial and temporal activity patterns. Moreover, we can not only reproduce the observed data with a lower dimensional representative, but also project spatio-temporal activity patterns in the same coordinate system. With the K-means clustering algorithm, five significant types of clusters that are directly annotated with a combination of temporal activities can be obtained, providing a clear picture of the correlation between the groups of regions and different activities at different times during a day. Besides the commercial and transportation dominant areas, we also detected two kinds of residential areas, the developed residential areas and the developing residential areas. We further interpret the spatial distribution of these clusters using urban form analytics. The results are highly consistent with the government planning in the same periods, indicating that our model is applicable to infer the functional regions from social media check-in data and can benefit a wide range of fields, such as urban planning, public services, and location-based recommender systems.     

中国5A级旅游景区空间分布结构研究

运用最邻近指数和地理集中指数对5A级旅游景区空间结构进行测定,结果表明,其空间结构呈集聚型分布,且人文旅游景区分布的集中程度要高于自然旅游景区;借助相关性计算,研究了社会经济和旅游业的发展水平对其空间分布结构的影响,提出了更合理地布局5A级旅游景区的方案。     

大连市旅游信息系统设计与开发

基于Google Maps API所提供的接口,把Google地图嵌入到自己的网页中,利用API提供的函数导入所需要的电子地图,实现了地图浏览和旅游信息显示等基本内容,并完成在电子地图上对旅游景点、旅游线路、旅游景区等信息的标注,使游客能够方便快捷地获取旅游景点及附近信息,从而合理安排旅游计划。     

Trajectory analysis at intersections for traffic rule identification

In this paper,we focus on trajectories at intersections regulated by various regulation types such as traffic lights,priority/yield signs,and right-of-way rules.We test some methods to detect and recognize movement patterns from GPS trajectories,in terms of their geometrical and spatio-temporal components.In particular,we first find out the main paths that vehicles follow at such locations.We then investigate the way that vehicles follow these geometric paths(how do they move along them).For these scopes,machine learning methods are used and the performance of some known methods for trajectory similarity measurement(DTW,Hausdorff,and Fréchet distance)and clustering(Affinity propagation and Agglomerative clustering)are compared based on clustering accuracy.Afterward,the movement behavior observed at six different intersections is analyzed by identifying certain movement patterns in the speed-and time-profiles of trajectories.We show that depending on the regulation type,different movement patterns are observed at intersections.This finding can be useful for intersection categorization according to traffic regulations.The practicality of automatically identifying traffic rules from GPS tracks is the enrichment of modern maps with additional navigation-related information(traffic signs,traffic lights,etc.).     

Spatiotemporal analysis of photo contribution patterns to Panoramio and Flickr

ABSTRACT

Photo-sharing services provide a rich resource of crowdsourced spatial data consisting of georeferenced imagery and metadata. Shared photos can provide valuable information for a variety of applications and geospatial analysis tasks, such as identifying tourist hot spots or traveled routes. Understanding the spatiotemporal patterns of photo contributions will allow analysts to assess the suitability of these data for related analysis tasks. Using California as a study area, this paper analyzes various aspects of photo contribution patterns of Panoramio and Flickr. It identifies areas where annual photo contributions are still growing and areas that undergo a decline in annual contributions. Multiple regression is used to identify which environmental correlates are associated with an increase in photo-sharing activities. Furthermore, panel data of annual contributions between 2006 and 2013 for California subcounties will be used in a regression model to demonstrate that there is a positive feedback effect between Panoramio and Flickr photo contributions, but no neighborhood effect. The results of this paper provide insight into the data quality of crowdsourced image collections. These collections are commonly used for geospatial applications, including tourist information services and the computation of scenic routes.     

最短路径算法在旅游线路规划中的应用——以庐山为例

本文以庐山旅游风景区为例,以一日游为主题,结合旅游景区景点知名度和各景点的停留时间,改进了G IS中的最短路径算法,利用VC++分析旅游区内各个景点之间的最短路径关系,得出该旅游区内的三条较合理的不同主题的一日游路线。通过本文的研究,希望能加强对庐山风景区的开发力度,促进庐山风景区的发展,并最终能推广G IS在旅游线路规划中的应用。     

利用网络游记分析不同类型游客的旅游流网络特征差异——以云南省为例

旅游流网络分析对理解游客的目的地选择以及目的地在旅游流网络中承担的角色有重要意义。以中国云南省为例,基于网络游记数据挖掘游客的多维度偏好,并以此对游客聚类,进而划分出不同类型的游客群体。针对各类游客游记中的旅游目的地序列建立旅游流网络,并从多个角度分析各类游客旅游流网络的结构特征和各目的地节点的角色特征。结果表明,不同类别游客的旅游流网络在整体结构上各有特点,反映出旅游目的地不同的空间交互模式和网络中心化程度。此外,部分旅游目的地在不同类别旅游流网络中承担截然相反的角色。上述分析有助于优化旅游流网络中各节点的协作机制,辅助旅游目的地制定差异化的旅游产品。     

Visualizing population mobility from spatiotemporally aggregated mobile phone data via a 3D gradient approach

Population mobility patterns are important for understanding a city's rhythms. With the widespread use of mobile phones, population-based trajectories can be utilized to explore such mobility patterns. However, to protect personal privacy, mobile phone data must be de-identified by data aggregation within each spatiotemporal unit. In data acquired from mobile phones, population mobility features are still implicit in the spatiotemporally aggregated grid data. In this study, based on image-processing techniques, a two-step 3D gradient method is adopted to extract the movement features. The first step is to estimate the initial movement pattern in each spatiotemporal grid, and then to estimate the accumulated movement pattern within a time period around a geographical grid. This method can be applied adaptively to multi-scale spatiotemporal grid data. Using geospatial visualization methods, estimated motion characteristics such as velocity and flow direction can be made intuitive and integrated with other multiscale geospatial data. Furthermore, the correlation between the population mobility pattern and demographic characteristics, such as gender and age groups, can be analyzed with intuitive visualization. The implication of the visualization results can be used for understanding the human dynamics in a city, which can be beneficial for urban planning, transportation management, and socioeconomic development.     

面向城市导游的无缝服务研究

智能导游服务已从传统的单一景区导游发展为城市多景区导游,因此,包含了景区间导游和景区内导游两大部分;表现为更加注重面向散客服务、兼容多移动智能终端以应用程序（App）的方式运行。由于景区间导游和景区内导游往往自成系统,在游客进出景区的过程中存在着两种系统的切换,且主要采用手动方式完成,尚没有实现城市多景区导游过程的无缝衔接。为了应对这个挑战,本文设计了一个面向城市多景区的无缝导游服务模式,分析了其架构以及工作机制;并着重讨论了城市无缝导游服务的关键技术,如系统间无缝切换的条件,包含判断游客进入、离开景区等;以及导游服务过程无缝衔接的机制,包含导游动态数据结构的设计,游客游览需求、导游过程状态在多导游系统间的传递等。最后通过实例验证了该方法的有效性,作为新的导游服务模式,同时为动态集成已有的导游App提供了解决方法。     

Discovering Landmark Preferences and Movement Patterns from Photo Postings

This article presents a geovisual analytics approach to discovering people's preferences for landmarks and movement patterns from photos posted on the Flickr website. The approach combines an exploratory spatio‐temporal analysis of geographic coordinates and dates representing locations and time of taking photos with basic thematic information available through the Google Maps Web mapping service, and interpretation of the analyzed area. The article describes data aggregation and filtering techniques to reduce the size of the dataset and focuses on information addressing research questions. The results of analysis for the Seattle metropolitan area help to distinguish between sites that are occasionally popular among the photographers and can be considered as potential attractions from sites that are regularly visited and already known as city landmarks. The analysis of photographers' movements across the metropolitan area shows that most photographers' itineraries are short and highly localized.     

空间数据模糊聚类的有效性(英文)

The validity measurement of fuzzy clustering is a key problem. If clustering is formed, it needs a kind of machine to verify its validity. To make mining more accountable, comprehensible and with a usable spatial pattern, it is necessary to first detect whether the data set has a clustered structure or not before clustering. This paper discusses a detection method for clustered patterns and a fuzzy clustering algorithm, and studies the validity function of the result produced by fuzzy clustering based on two aspects, which reflect the uncertainty of classification during fuzzy partition and spatial location features of spatial data, and proposes a new validity function of fuzzy clustering for spatial data. The experimental result indicates that the new validity function can accurately measure the validity of the results of fuzzy clustering. Especially, for the result of fuzzy clustering of spatial data, it is robust and its classification result is better when compared to other indices.     

利用划分方法进行混合数据聚类

目前常用的几种基于划分的聚类方法主要处理数值型数据,能有效处理实际应用领域中常用的包括数值和符号混合数据的聚类算法则较少。基于此问题,文章根据k均值、k中心点和k众数等基于划分的聚类方法各自的特点,对其进行集成与改进,提出一种能够应用于混合类型数据的聚类分析方法,即将所有的混合类型变量转换到共同的标度区间[0.0,1....     

城际轨道建设对珠三角地区旅游空间格局的影响

近年来,快速发展的高速铁路、城际轨道等高速交通方式对旅游的影响日益显现。本文以珠三角地区运营和规划城际轨道为例,基于GIS网络分析技术和通达性指标,探讨了城际轨道通车前后对珠三角地区旅游空间格局的影响。结果表明:城轨开通将会产生显著的"时空压缩"效应,旅游景点总通达时间降幅达32.87%,旅游景点平均通达时间减少0.7 h;不同区域通达性水平提升具有差异性,城际轨道站点及其周边地区成为通达性水平提升最大的地区,随着与站点距离逐渐增加,通达性变化程度逐渐降低;城轨开通后各地区通达性水平差异逐渐缩小,并趋于均衡;城轨影响下的旅游景点通达性的影响具有"廊道效应"与"隧道效应"相结合的特征,空间格局由开通前的"中心-外围"态势向面状均衡分布格局转变。城际轨道带来的"时空压缩"效应,在扩大了旅游景点市场范围的同时,由于通行时间成本降低,进一步提高了旅游出行的效率。