地理信息志愿者信誉度评估的版本相似度模型&mdash;&mdash;以面目标为例

赵肄江; 周晓光

doi:10.11947/j.AGCS.2015.20140065

测绘学报 >

2015 , Vol. 44 >Issue 5: 578 - 584

DOI: https://doi.org/10.11947/j.AGCS.2015.20140065

地图学与地理信息

地理信息志愿者信誉度评估的版本相似度模型——以面目标为例

赵肄江 ,
周晓光

展开

1. 中南大学地球科学与信息物理学院, 湖南长沙 410083;
2. 湖南科技大学知识处理与网络化制造湖南省普通高校重点实验室, 湖南湘潭 411201

赵肄江(1980—),男,讲师,博士生,主要从事众源地理信息相关研究。E-mail: zyriver@gmail.com

收稿日期: 2014-01-28

修回日期: 2014-09-23

网络出版日期: 2015-05-27

基金资助

国家自然科学基金(41371366);国家863计划(2012AA121301);国家科技支撑计划(2012BAK12B01)

收起

Version Similarity-based Model for Volunteers' Reputation of Volunteered Geographic Information: A Case Study of Polygon

ZHAO Yijiang ,
ZHOU Xiaoguang

Expand

1. School of Geosciences and Info-physics, Central South University, Changsha 410083, China;
2. Key Laboratory of Knowledge Processing and Networked Manufacturing, Hunan University of Science and Technology, Xiangtan 411201, China

Received date: 2014-01-28

Revised date: 2014-09-23

Online published: 2015-05-27

Supported by

The National Natural Science Foundation of China (No. 41371366);The National High-tech Research and Development Program of China (863 Program) (No. 2012AA121301); The National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No. 2012BAK12B01)

Fold

摘要

针对自发地理信息中存在大量恶意、虚假、低质量数据,提出了一种基于版本相似度的VGI志愿者信誉度计算模型。该模型将每个志愿者对某个地理空间目标的一次编辑结果定义为一个版本,当其他用户编辑该目标版本时,通过计算版本相似度来获得其他用户对该志愿者这个目标版本的支持度;然后通过计算其他贡献者对某志愿者所贡献的每个目标的支持度,对所有目标的支持度进行加权平均获得该志愿者的综合信誉度。其中版本相似度综合目标空间和属性相似性的主要因素进行加权计算。然后以面目标为例阐述了本文志愿者信誉度计算过程。为了验证本文信誉度计算模型的合理性,笔者采用德国柏林OpenStreetMap数据进行试验,试验表明通过本文模型计算获得的用户信誉度与其贡献的要素质量总体上正相关。

关键词： 自发地理信息; 信誉度计算模型; 版本相似度; OpenStreetMap

本文引用格式

赵肄江 , 周晓光 . 地理信息志愿者信誉度评估的版本相似度模型——以面目标为例[J]. 测绘学报, 2015 , 44(5) : 578 -584 . DOI: 10.11947/j.AGCS.2015.20140065

Abstract

At present, it is difficult to evaluate the quality of volunteered geographic information(VGI), which have malicious, false, and poor quality data. Therefore, a version similarity-based reputation model for volunteers of VGI system is proposed. In the model, each editing to a geographic spatial object of each volunteer is defined as a version. When the object version is modified by other users, support degree of the version is computed through version similarity. Then, support degree of every object contributed by a volunteer is calculated according by others' modifications. The volunteer's reputation is obtained through weighted average of all his support degrees. The version similarity composites major factors of spatial similarity and attributes similarity between versions of a same object. Polygon objects are employed as an example to describe the computation process of volunteer reputation of our model. For verifying and analyzing the rationality of our reputation model, Berlin's historical data from OpenStreetMap are used for experiments. It shows that users' reputation calculated by our model has a positive correlation with quality of objects contributed by them as a whole.

Key words： volunteered geographic information; reputation evaluation model; version similarity; OpenStreetMap

参考文献

[1] GOODCHILD M F. Citizens as Sensors: The World of Volunteered Geography[J]. GeoJournal, 2007, 69(4): 211-221.
[2] LI Deren, SHAO Zhenfeng. On New Geographic Information Age[J]. Science China: Information Sciences, 2009, 39(6): 579-587. (李德仁, 邵振峰. 论新地理信息时代[J]. 中国科学: 信息科学), 2009, 39(6): 579-587.)
[3] GOODCHILD M F, LI Linna. Assuring the Quality of Volunteered Geographic Information[J]. Spatial Statistics, 2012, 1: 110-120.
[4] QIAN Xinlin. Research on the Representation and Management of Geospatial Data from Volunteered Geographic Information[D]. Wuhan: Wuhan University, 2011. (钱新林. 面向自发地理信息的空间数据表达与管理方法研究[D]. 武汉: 武汉大学, 2011.)
[5] CHEN Shuyan. A Web-based Accessibility Analysis Service Using OpenStreetMap Data[D]. Shanghai: Shanghai Normal University, 2010. (陈舒燕. 基于 OpenStreetMap 的出行可达性分析与实现[D]. 上海: 上海师范大学, 2010.)
[6] ZOOK M, GRAHAM M, SHELTON T, et al. Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake[J]. World Medical & Health Policy, 2010, 2(2): 7-33.
[7] HU Qingwu, WANG Ming, Li Qingquan. Urban Hotspot and Commercial Area Exploration with Check-in Data[J]. Acta Geodaetica et Cartographica Sinica, 2014,43(3): 314-321. (胡庆武, 王明, 李清泉. 利用位置签到数据探索城市热点与商圈[J]. 测绘学报, 2014,43(3): 314-321.)
[8] ZHANG Hongping, GU Xueyun, XIONG Ping, et al. Development and Application of Volunteered Geographic Information[J]. Geomatics World,2012, 10(4): 67-71. (张红平, 顾学云, 熊萍, 等. 志愿者地理信息研究与应用初探[J]. 地理信息世界, 2012, 10(4): 67-71.)
[9] FLANAGIN A J, METZGER M J. The Credibility of Volunteered Geographic Information[J]. GeoJournal, 2008, 72(3-4): 137-148.
[10] VAN EXEL M, DIAS E, FRUIJTIER S. The Impact of Crowdsourcing on Spatial Data Quality Indicators[C]//Proceedings of the 6th GIScience International Conference on Geographic Information Science. Zurich, Switzerland[s.n.], 2010: 213-216.
[11] HAKLAY M. How Good Is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets[J]. Environment and Planning B: Planning & Design, 2010, 37(4): 682.
[12] GIRRES J F, TOUYA G. Quality Assessment of the French OpenStreetMap Dataset[J]. Transactions in GIS, 2010, 14(4): 435-459.
[13] KEβLER C, DE GROOT R T A. Trust as a Proxy Measure for the Quality of Volunteered Geographic Information in the Case of OpenStreetMap[M]//Geographic Information Science at the Heart of Europe. Berlin: Springer, 2013: 21-37.
[14] BISHR M, MANTELAS L. A Trust and Reputation Model for Filtering and Classifying Knowledge about Urban Growth[J]. GeoJournal, 2008, 72(3-4): 229-237.
[15] HAO Yanling, TANG Wenjing, ZHAO Yuxin, et al. Areal Feature Matching Algorithm Based on Spatial Similarity[J]. Acta Geodaetica et Cartographica Sinica, 2008, 37(4): 501-506. (郝燕玲, 唐文静, 赵玉新, 等. 基于空间相似性的面实体匹配算法研究. 测绘学报, 2008, 37(4): 501-506.)
[16] TANG Luliang, LI Qingquan, YANG Bisheng. Similarity Measuring for Multi-resolution Transmission of Spatial Datasets over the Internet[J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(4): 336-340. (唐炉亮, 李清泉, 杨必胜. 空间数据网络多分辨率传输的几何图形相似性度量[J]. 测绘学报, 2009, 38(4): 336-340.)
[17] MASUYAMA A. Methods for Detecting Apparent Differences between Spatial Tessellations at Different Time Points[J]. International Journal of Geographical Information Science, 2006, 20(6): 633-648.
[18] AI Tinghua, SHUAI Yun, LI Jingzhong. A Spatial Query Based on Shape Similarity Cognition[J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(4): 356-362. (艾廷华, 帅赟, 李精忠. 基于形状相似性识别的空间查询[J]. 测绘学报, 2009, 38(4): 356-362.)
[19] FU Zhongliang, LU Yuefeng. Establishment of the Comprehensive Model for Similarity of Polygon Entity by Using the Bending Radius Complex Function[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(1): 145-151. (付仲良, 逯跃锋. 利用弯曲度半径复函数构建综合面实体相似度模型[J]. 测绘学报, 2013, 42(1): 145-151.)
[20] AN Xiaoya, SUN Qun, XIAO Qiang, et al. A Shape Multi-level Description Method and Application in Measuring Geometry Similarity of Multi-scale Spatial Data[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(4): 495-501. (安晓亚, 孙群, 肖强, 等. 一种形状多级描述方法及在多尺度空间数据几何相似性度量中的应用[J]. 测绘学报, 2011, 40(4): 495-501.)
[21] ARKIN E M, CHEW L P, HUTTENLOCHER D P, et al. An Efficiently Computable Metric for Comparing Polygonal Shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(3): 209-216.
[22] FAN H, ZIPF A, FU Q, et al. Quality Assessment for Building Footprints Data on OpenStreetMap[J]. International Journal of Geographical Information Science, 2014, 28(4): 700-719.

Options

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献