Personalized travel route recommendation using collaborative filtering based on GPS trajectories

Travelling is a critical component of daily life. With new technology, personalized travel route recommendations are possible and have become a new research area. A personalized travel route recommendation refers to plan an optimal travel route between two geographical locations, based on the road networks and users’ travel preferences. In this paper, we define users’ travel behaviours from their historical Global Positioning System (GPS) trajectories and propose two personalized travel route recommendation methods – collaborative travel route recommendation (CTRR) and an extended version of CTRR (CTRR+). Both methods consider users’ personal travel preferences based on their historical GPS trajectories. In this paper, we first estimate users’ travel behaviour frequencies by using collaborative filtering technique. A route with the maximum probability of a user’s travel behaviour is then generated based on the naïve Bayes model. The CTRR+ method improves the performances of CTRR by taking into account cold start users and integrating distance with the user travel behaviour probability. This paper also conducts some case studies based on a real GPS trajectory data set from Beijing, China. The experimental results show that the proposed CTRR and CTRR+ methods achieve better results for travel route recommendations compared with the shortest distance path method.     

LBS中基于轨迹的用户行为特征分析

LBS的发展趋势是向用户提供智能化、个性化的位置服务。以用户行为轨迹数据为基础,进行轨迹简化、POI匹配、时空融合、习惯分析等处理,建立起用户行为特征模型,从而实现向不同用户提供个性化位置服务。     

Measuring the Reliability of Wheelchair User Route Planning based on Volunteered Geographic Information

The development of a wheelchair user friendly route planning application inherits a number of special requirements and details that need to be considered during the generation of the routing graph and the corresponding algorithm, making this task much more complex than car or pedestrian related applications. Each wheelchair type and, more importantly, each individual user might have different needs with regards to the way condition or other criteria. This study proposes a new approach to route planning for wheelchair users tailored for individual and personal requirements provided by the user and the calculation of a reliability factor of the computed wheelchair path. The routing graph is based on the freely available Volunteered Geographic Information (VGI) retrieved from the OpenStreetMap (OSM) project. The newly created algorithm is evaluated and tested for a selected area in Bonn, Germany. A new reliability factor is introduced that gives direct feedback about the quality of the generated path. Similar factor estimations can also be utilized for multiple route planning applications where VGI or other commercial or administrative data is implemented and more detailed factors than a simple geometric representation of a street network are of importance.     

Collaborative personalized multi‐criteria wayfinding for wheelchair users in outdoors

While finding the optimal route for users with physical disabilities and personalizing routes for each user, on the one hand, and collaborative wayfinding, on the other hand, have been addressed in the pedestrian navigation systems literature, there has not been much research on combining the two activities. The problem associated with wayfinding approaches solely based on information about network segments and personal preferences is that the information about segments in the database may not, correctly and/or adequately address user preferences. The problem associated with wayfinding approaches solely based on the ratings given to routes by wheelchair users is the lack of rates (or scores) for all possible routes between all possible origin‐destination pairs in the network. This article discusses an approach to combine these two approaches for wayfinding to augment each other's shortcomings. To evaluate the personalized wayfinding approach, we utilize a route index, called a comparison index. The results show that with a P‐value of 9%, the routes obtained from our approach are more accessible than the routes obtained from another approach developed in another study. To evaluate the collaborative wayfinding approach, a Monte Carlo simulation was conducted which reflects the updates in routes as users' feedbacks become available.     

一种基于遗传算法的多模式多标准路径规划方法

单一路径评价标准难以满足日益多样化的出行路径规划需求。多标准路径规划成为公众出行服务的研究热点。然而,多标准路径规划本质上是具有NP特性的多标准决策问题,且涉及多种交通出行模式。多个不同标准的权重设置将直接影响路径规划结果。因此,如何科学合理地设置不同标准的权重成为多标准路径规划中的技术瓶颈。本文提出了一种适应多模式交通网络环境的多标准路径规划方法,借鉴遗传算法在求解多标准优化问题中的优势,将其扩展到多模式多标准路径规划中。该方法避免了不同出行标准权重设置中的主观性和不确定性,能够实现更为灵活的交通出行模式自动化组合,为出行者提供满足个性化需求的、多标准的出行路径规划服务。     

Impact of proximity-adjusted preferences on rank-order stability in geographical multicriteria decision analysis

This paper presents a new approach to deriving preferences assigned to evaluation criteria in geographical multicriteria decision analysis. In this approach, the preferences, expressed by numeric weights, are adjusted by distance measures derived from the explicit consideration of a locational structure. The structure is given by locations of decision options and high importance reference objects. The approach is demonstrated on the example of a house selection case study in San Diego, California. The results show that proximity-adjusted preferences for the evaluation criteria can alter significantly the rank order of decision options. Consequently, the explicit modeling of spatial preference variability may be needed in order to better account for decision-maker’s preferences.     

基于有向层次模型的城市常规公交出行路径优化

基于GIS多层次的公共交通实体数据模型,引入了基于距离的换乘延误,对公交网络要素属性逐步更新,提出了以换乘可比距离为依据、循环优化的分析方法。城市公共交通规划中的分配模型及出行优化过程中都需要考虑公交换乘问题,传统的处理方式一般不考虑换乘延误或采用平均换乘延误进行估算,难以精确地获得最优公交出行路径的换乘信息。基于空间数据建模技术,可以对公交实体要素进行多层次表达,其中有向层次数据模型为精确计算换乘延误提供了可能。     

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。     

A comparison of usefulness of 2D and 3D representations of urban planning

Very little existing literature has addressed the issues of the perceived usefulness of 3D visualizations over 2D and the use of cartographic shadow representations in the planning community. Urban planning has moved toward a 3D, geographic-information-system-centric, and functional decision support framework. This study aims to examine the preferences of urban planning professionals with respect to 2D and 3D visualizations in a case study. The authors built a 3D representation of a proposed building along with the existing urban environment in Queenstown, New Zealand and conducted a usefulness test through a survey and interview. Based on the survey, the study evaluated the degree of task utility perceived in each visualization method, the effect on the mental image, and shadow representation preferences. The findings support the literature that the benefits of using a 2D or 3D model are closely related to the types of planning tasks undertaken. The findings also reveal a complex view of planning activities, suggesting that planners themselves cannot be treated as a single group for research purposes.     

导航电子地图主动表达模型研究

目前,导航电子地图"千人一面"的服务模式不能满足用户追求个性的时代特点。文中从用户因素和时空环境两方面对导航电子地图内容主动表达的影响因子进行深入研究,建立导航电子地图主动表达模型。与传统表达模式相比,主动表达模式关注特定时空环境下用户的个性和偏好,对有不同的认知特征和不同导航任务的用户在不同环境下采取不同的表达策略,服务质量有所提高。     

城市街区和签到数据结合的个性化城市兴趣区域推荐方法

利用社交媒体用户的历史签到数据分析用户空间活动偏好实现用户兴趣区域推荐,在城市商业规划中起着重要作用,也为了解人们的城市生活和需求提供帮助。已有方法获得的ROI具有模糊性和多样性,无法给ROI赋予准确的地理描述信息,对用户来说可解释性不强。因此,本文提出了一种结合城市街区和签到数据的个性化兴趣区域推荐方法(CBCD),引入城市街区概念解决ROI边界模糊问题。首先,通过城市道路网生成城市街区,并将大规模签到数据映射到城市街区转换为区域签到;然后,基于区域签到对用户空间活动偏好和类别偏好分别进行个性化建模;最后,融合空间和类别活动偏好,向用户推荐其可能感兴趣的区域。在真实的数据集上进行试验,结果表明该方法具有较高的推荐精度,对用户感兴趣城市街区的挖掘和推荐具有一定的价值。     

A weighted multi-attribute method for matching user-generated Points of Interest

To a large degree, the attraction of Big Data lies in the variety of its heterogeneous multi-thematic and multi-dimensional data sources and not merely its volume. To fully exploit this variety, however, requires conflation. This is a two-step process. First, one has to establish identity relations between information entities across different data sources; and second, attribute values have to be merged according to certain procedures that avoid logical contradictions. The first step, also called matching, can be thought of as a weighted combination of common attributes according to some similarity measures. In this work, we propose such a matching based on multiple attributes of Points of Interest (POI) from the Location-based Social Network Foursquare and the local directory service Yelp. While both contain overlapping attributes that can be used for matching, they have specific strengths and weaknesses that make their conflation desirable. For instance, Foursquare offers information about user check-ins to places, while Yelp specializes in user-contributed reviews. We present a weighted multi-attribute matching strategy, evaluate its performance, and discuss application areas that benefit from a successful matching. Finally, we also outline how the established POI matches can be stored as Linked Data on the Semantic Web. Our strategy can automatically match 97% of randomly selected Yelp POI to their corresponding Foursquare entities.     

基于文本挖掘的个性化地图服务模型研究

随着个性化地图服务的深入研究,如何获取更加实时可靠的用户个性化信息和需求,成为当前研究的难点。本文从人们最重要的交流工具——文本数据出发,在当前文本挖掘技术的支持下,提出了一种能够识别挖掘用户所言,分析提取用户所需,并最终实现地图可视化的个性化地图服务模型。通过实例验证,该模型能够有效地提取地图知识和用户信息,为个性化地图服务的发展提供技术和数据支撑。     

Map-Based Exploratory Evaluation of Non-Medical Determinants of Population Health

Multi‐criteria evaluation (MCE) and decision‐making are increasingly combined with interactive tools to assist users with visual thinking and exploring decision strategies. The interactive control of criterion combination rules and the simultaneous observation of geographic space and criterion space provide a means of investigating the sensitivity of the decision outcome to the decision‐maker's preferences. The Analytic Hierarchy Process (AHP) is an MCE method that has been successfully implemented in management processes including those addressed by Geographic Information Systems. In this paper, we present a map‐based, interactive AHP implementation, which provides a link between a well‐understood decision support method and exploratory geographic visualization. Using a case study with public health data for the Province of Ontario, Canada, we demonstrate that exploratory map use increases the effectiveness of the AHP‐based evaluation of population health.     

Web-enabled spatial decision analysis using Ordered Weighted Averaging (OWA)

 This paper presents a spatial decision support tool that implements the Ordered Weighted Averaging (OWA) method. OWA is a family of multicriteria evaluation operators characterised by two sets of weights: criterion importance weights and order weights. We propose a highly interactive way of choosing, modifying, and fine-tuning the decision strategy defined by the order weights. This exploratory approach to OWA is supported by a graphical representation of the operator's behaviour in terms of decision risk and tradeoff/dispersion between criteria. Our prototype implementation is based on the CommonGIS software, and thus, Web-enabled and working with vector data. We successfully demonstrate online, exploratory support of spatial decision strategies using a data set of skiing resorts in Wallis, Switzerland. Received: 24 September 2002 / Accepted: 10 January 2003     

Geospatial modelling for identification of potential ecological corridors in Orissa

Development of forest connectivity and corridors are critical for biodiversity conservation and also ensures energy and genetic exchange across greater spatial extent. A model has been developed to geospatially identify the potential ecological corridors based on the vegetation type and land cover data in association with spatial disturbance profile. The model formulates the route of least impedance due to (1) disturbance (a function of fragmentation, juxtaposition, Interspersion & proximity to roads/settlements) and (2) vegetation type and land cover. This is because the movement of genetic information and materials follow the path of least resistance across a landscape. The paper explores the utility of the approach to spatially generate ecological corridors connecting 14 protected areas of Orissa. The model has been able to identify the potential route connecting the different protected regions with 85–87% of the corridor in the natural areas. Of the 14 protected areas, only 12 could be connected by the model as they confirm to the criteria for the corridor establishment.     

基于GIS的OWA方法在城市防灾规划中的应用

作为一个多准则评价的相对较新概念,基于GIS的OWA方法可以通过权重计算产生多种决策策略。分析了OWA方法与布尔决策和权重线性叠加（WLC）等多准则评价方法在决策策略上的区别,介绍了依据次序重要性来计算次序权重和应用层次分析程序（AHP）构建比较矩阵来计算准则权重的方法,并应用于唐山市防灾规划,计算了唐山市地质灾害影响下的土地利用适宜度。在分析计算结果的基础上,为唐山市土地资源的合理开发提出了建议。     

A web‐based visualization tool for exploring stakeholder conflicts in land‐use planning

This article describes an open source web‐based visualization tool for exploring stakeholder conflicts in land‐use planning. It implements a multi‐criteria, decision‐analytic framework which solves a conflict‐constrained knapsack problem in order to find Pareto efficient combinations of actions which maximize public value, given the conflict constraint. The user interface is centered around an interactive map in which geographical subareas are color‐shaded in proportion to the mean strength of preference for a particular chosen action within the population in the selected area. The aim of this work is to investigate the use of web technologies and formal problem‐solving methods for improving public participation in land‐use planning and support local governments in the pursuit of improved decision‐making. The tool was developed using the free statistical programming language R and the web application framework Shiny. Its usefulness is demonstrated through a case study in Upplands Väsby municipality in Stockholm County, Sweden. The article ends with a summary together with some ideas for future research and development.     

A multi‐criteria decision‐making approach for geometric matching of areal objects

We propose a method for geometric areal object matching based on multi‐criteria decision making. To enable this method, we focused on determining the matched areal object pairs that have all relations, one‐to‐one relationships to many‐to‐many relationships, in different spatial data sets by fusing geometric criteria without user invention. First, we identified candidate corresponding areal object pairs with a graph‐based approach in training data. Second, three matching criteria (areal hausdorff distance, intersection ratio, and turning function distance) were calculated in candidate corresponding pairs and these criteria were normalized. Third, the shape similarity was calculated by weighted linear combination using the normalized matching criteria (similarities) with the criteria importance through intercriteria correlation method. Fourth, a threshold (0.738) of the shape similarity estimated in the plot of precision versus recall versus all possible thresholds of training data was applied, and the matched pairs were determined and identified. Finally, we visually validated the detection of similar areal feature pairs and conducted statistical evaluation using precision, recall, and F‐measure values from a confusion matrix. Their values were 0.905, 0.848, and 0.876, respectively. These results validate that the proposed classifier, which detects 87.6% of matched areal pairs, is highly accurate.