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1.
The relevance of geographic information has become an emerging problem in geographic information science due to an enormous increase in volumes of data at high spatial, temporal, and semantic resolution, because of ever faster rates of new data capturing. At the same time, it is not clear whether the concept of relevance developed in information science and implemented for document-based information retrieval can be directly applied to this new, highly dynamic setting. In this study, we analyze the criteria users apply when judging the relevance of geographic entities in a given mobile usage context. Two different experiments have been set up in order to gather users' opinions on a set of possible criteria, and their relevance judgements in a given scenario. The importance ascribed to the criteria in both experiments clearly implies that a new concept of relevance is required when dealing with geographic entities instead of digital documents. This new concept of ‘Geographic Relevance’ is highly dependent on personal mobility and user's activity, whose understanding may in turn be refined by the assimilation of ‘Geographic Relevance’ itself.  相似文献   

2.
廖伟华  聂鑫 《热带地理》2018,38(6):751-758
同位模式表示不同类型的实体在空间邻域内共同频繁出现的规律,是城市实体空间关联的主要表达形式,但不能挖掘出指定实体的空间关联,需要寻找新的计算方法。在城市计算的视角下,通过引入粗糙集研究城市空间关联问题发现：1）该方法能把复杂的地理空间关联问题转换成信息决策问题,在信息决策表中计算城市实体之间的空间关联等拓扑关系,计算过程和结果可以挖掘城市行业之间的空间集聚和关联问题。2）通过属性约简得到属性核可以把高维空间数据降维,找到影响空间关联的重要因子。3）该方法拓宽了城市计算的理论方法体系和粗糙集方法的行业应用。最后,通过Python爬取南宁市城市服务业数据,进行方法的验证,计算结果与成熟的Apriori算法结果,以及南宁市服务业空间关联实际情况基本一致,证明了粗糙空间关联方法的可行性和正确性。  相似文献   

3.
ABSTRACT

Defining and identifying duplicate records in a dataset is a challenging task which grows more complex when the modeled entities themselves are hard to delineate. In the geospatial domain, it may not be clear where a mountain, stream, or valley ends and begins, a problem carried over when such entities are catalogued in gazetteers. In this paper, we take two gazetteers, GeoNames and SwissNames3D, and perform matching – identifying records in each that are about the same entity – across a sample of natural feature records. We first perform rule-based matching, establishing competitive results, then apply machine learning using Random Forests, a method well-suited to the matching task. We report on the performance of a wider array of matching features than has been previously studied, including domain-specific ones such as feature type, land cover class, and elevation. Our results show an increase in performance using machine learning over rules, with a notable performance gain from considering feature types, but negligible gains from other specialized matching features. We argue that future work in this area should strive to be more reproducible and report results on a realistic testing pipeline including candidate selection, feature extraction, and classification.  相似文献   

4.
推荐系统是帮助互联网用户克服信息过剩的有效工具。在地学数据共享领域,较其他物品的内容属性,地学数据具有更加丰富的时空属性,这也给地学数据推荐带来挑战。针对地学数据的特点,为地学数据共享推荐服务开发了一种动态加权的混合过滤方法。该方法分别采用协同过滤和基于内容过滤算法预测用户对数据的兴趣度,再以训练模型计算最优加权权重,计算最终预测评分。在数据获取阶段,通过用户访问日志数据,采用Jenks Natural Break算法分析用户访问记录获取用户的数据兴趣度。在基于内容过滤部分,通过数据的空间、时间及内容属性计算数据相似度,并以用户历史行为为依据计算用户兴趣。在协同过滤和基于内容过滤中分别采用k-NN算法计算用户对未访问数据的预测评分,并进行加权求和。通过训练集,对理想权重值及用户的共同评价度（co-rating level）进行建模,拟合二者的关系。该模型被应用于混合过滤的权重调整,以获得最优的加权方程。测试结果显示,结合数据时空属性的混合过滤方法的准确度和召回率,较单一的协同过滤或基于内容过滤方法有显著提高。  相似文献   

5.
Traditional spatial clustering methods have the disadvantage of "hardware division",and can not describe the physical characteristics of spatial entity effectively.In view of the above,this paper sets forth a general multi-dimensional cloud model,which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry.Based on infrastructures' classification and demarcation in Zhanjiang,a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering,the comparative study of Fuzzy C-means and a coupled analysis of residential land prices.General multi-dimensional cloud model reflects the integrated characteristics of spatial objects better,reveals the spatial distribution of potential information,and realizes spatial division more accurately in complex circumstances.However,due to the complexity of spatial interactions between geographical entities,the generation of cloud model is a specific and challenging task.  相似文献   

6.
This paper describes analyses involving patterned string bags collected in the upper Sepik in Papua New Guinea. The Mantel test and correspondence analysis were used to explore whether variability in craft repertoires exhibits any covariance with the region's complex linguistic picture, and if so, whether this relationship is more significant than any spatial autocorrelation the data may exhibit. Bag construction techniques exhibited strong spatial autocorrelation, while for colour patterns the effect was weaker. An effect for language remained for both dependents after statistical control, but colour pattern characteristics had a slightly stronger association with language overall. The weaker spatial autocorrelation for colour pattern variability is argued to be due to higher rates of dissemination facilitated by the visibility of the patterns and their compatibility with a broad range of construction techniques. The effect for language, on the other hand, is argued to have resulted from of a higher rate of inter-settlement migration along a particular stretch of the Sepik where people speak the same language.  相似文献   

7.
A review of quantitative methods for movement data   总被引：1，自引：0，他引：1  
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8.
Geographical entities are characterized by rather complex structures. They involve space and thematic information, which is subject to change in time, while history should be maintained. On the other hand, these structures may be irregular (i.e. they do not necessarily conform to a fixed schema), because associated data is usually collected based on different specifications and multiple resolutions. Hence, the representation of geographical entities in traditional data models, such as the relational or object-oriented, is not always feasible. In this respect, this paper investigates the use of semi-structured data (SSD) models—an innovative approach recently developed in Information Technology—for modelling dynamic geographical entities. A framework for the representation of geographic entities in Object Exchange Model (OEM), a popular model for semi-structured data, is introduced. Additionally, it is shown how useful information can be extracted from such a representation using the LOREL query language for SSD. A simplified case study in the application domain of cadastre involving SSD is examined closely.  相似文献   

9.
Existing sensor network query processors (SNQPs) have demonstrated that in-network processing is an effective and efficient means of interacting with wireless sensor networks (WSNs) for data collection tasks. Inspired by these findings, this article investigates the question as to whether spatial analysis over WSNs can be built upon established distributed query processing techniques, but, here, emphasis is on the spatial aspects of sensed data, which are not adequately addressed in the existing SNQPs. By spatial analysis, we mean the ability to detect topological relationships between spatially referenced entities (e.g. whether mist intersects a vineyard or is disjoint from it) and to derive representations grounded on such relationships (e.g. the geometrical extent of that part of a vineyard that is covered by mist). To support the efficient representation, querying and manipulation of spatial data, we use an algebraic approach. We revisit a previously proposed centralized spatial algebra comprising a set of spatial data types and a comprehensive collection of operations. We have redefined and re-conceptualized the algebra for distributed evaluation and shown that it can be efficiently implemented for in-network execution. This article provides rigorous, formal definitions of the spatial data types, points, lines and regions, together with spatial-valued and topological operations over them. The article shows how the algebra can be used to characterize complex and expressive topological relationships between spatial entities and spatial phenomena that, due to their dynamic, evolving nature, cannot be represented a priori.  相似文献   

10.
Traditional spatial clustering methods have the disadvantage of “hardware division”, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures’ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated characteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.  相似文献   

11.
讨论位置感知计算中定位信息表达存在的不足,引入自然语言描述作为补充,介绍自然语言中的空间概念,并分析了影响空间定位信息向自然语言转换的因素,归纳为尺度依赖、方向依赖和身份依赖,讨论制约因素影响下的参考框架、参考点和方位词的选择,并以地图作为空间转化媒介,给出一组人们日常使用的定位描述句式,最后以车辆监控系统和图书馆导航为测试平台,针对室外和室内两种不同应用环境进行了自然语言描述实验.  相似文献   

12.
Map databases traditionally capture snapshot representations of the world following strict data collection and representation guidelines. The content of these map databases is often assessed using data quality metrics focusing on accuracy, completeness and consistency. The success of volunteered geographic information, supporting evolving representations of the world based on fluid guidelines, has rendered these measures insufficient. In this paper, we address the need to capture the variability in quality of a map database. We propose a new spatial data quality measure – dataset maturity – enabling assessment of the database based on temporal trends in feature definitions, specifically geometry-type definitions. The proposed measure can be (1) efficiently used to identify feature definition patterns reflecting community consensus that could be formalised in community guidelines and (2) deployed to identify regions that would benefit from increased editorial activity to achieve greater map homogeneity. We demonstrate the measure based on the content of the OpenStreetMap database in four regions of the world and show how the proposed dataset maturity measure captures a distinct quality of the datasets, distinct to data completeness and consistency.  相似文献   

13.
《The Journal of geography》2012,111(6):277-286
  相似文献   

14.
Traditional spatial clustering methods have the disadvantage of “hardware division“, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures’ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated characteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.  相似文献   

15.
Local search services allow a user to search for businesses that satisfy a given geographical constraint. In contrast to traditional web search engines, current local search services rely heavily on static, structured data. Although this yields very accurate systems, it also implies a limited coverage, and limited support for using landmarks and neighborhood names in queries. To overcome these limitations, we propose to augment the structured information available to a local search service, based on the vast amount of unstructured and semi‐structured data available on the web. This requires a computational framework to represent vague natural language information about the nearness of places, as well as the spatial extent of vague neighborhoods. In this paper, we propose such a framework based on fuzzy set theory, and show how natural language information can be translated into this framework. We provide experimental results that show the effectiveness of the proposed techniques, and demonstrate that local search based on natural language hints about the location of places with an unknown address, is feasible.  相似文献   

16.
There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities.  相似文献   

17.
Recent developments in sensing and tracking technologies have enabled large geographical databases to be established that represent spatial dynamics of ‘behavioral entities’. Within this type of dynamics there are several levels and modes of organization that need to be revealed. Clusters are high‐level groupings of entities, where change in their location and form, including split and merge events, represents self‐organization and functioning patterns. Such information may contribute for better understanding spatially complex dynamic patterns. The main objective of this article is to develop an adaptable methodology that facilitates exploration of spatial order and processes in point pattern dynamics. The approach presented here utilizes data‐clustering at each snapshot of the moving pattern, and then involves pairwise linking between the clusters identified at each snapshot and those identified in the following snapshot. Such linking is based on a new methodology that defines well globally optimized solutions for numerous possible linking combinations based on Linear Programming. A preliminary assessment of the approach was conducted with an existing Ants' simulation tool, capable of creating data sets covering in detail a substantial portion of the nest's life cycle.  相似文献   

18.
Mobile devices are becoming very popular in recent years, and large amounts of trajectory data are generated by these devices. Trajectories left behind cars, humans, birds or other objects are a new kind of data which can be very useful in the decision making process in several application domains. These data, however, are normally available as sample points, and therefore have very little or no semantics. The analysis and knowledge extraction from trajectory sample points is very difficult from the user's point of view, and there is an emerging need for new data models, manipulation techniques, and tools to extract meaningful patterns from these data. In this paper we propose a new methodology for knowledge discovery from trajectories. We propose through a semantic trajectory data mining query language several functionalities to select, preprocess, and transform trajectory sample points into semantic trajectories at higher abstraction levels, in order to allow the user to extract meaningful, understandable, and useful patterns from trajectories. We claim that meaningful patterns can only be extracted from trajectories if the background geographical information is considered. Therefore we build the proposed methodology considering both moving object data and geographic information. The proposed language has been implemented in a toolkit in order to provide a first software prototype for trajectory knowledge discovery.  相似文献   

19.
  相似文献   

20.
In this article, we present the GeoCorpora corpus building framework and software tools as well as a geo-annotated Twitter corpus built with these tools to foster research and development in the areas of microblog/Twitter geoparsing and geographic information retrieval. The developed framework employs crowdsourcing and geovisual analytics to support the construction of large corpora of text in which the mentioned location entities are identified and geolocated to toponyms in existing geographical gazetteers. We describe how the approach has been applied to build a corpus of geo-annotated tweets that will be made freely available to the research community alongside this article to support the evaluation, comparison and training of geoparsers. Additionally, we report lessons learned related to corpus construction for geoparsing as well as insights about the notions of place and natural spatial language that we derive from application of the framework to building this corpus.  相似文献   

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