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An agent-based and quality-aware integration of geo-social networks data - data integration as a collaborative negotiation process

基于代理和质量感知的地理社交网络数据集成 - 数据集成作为协作协商过程

基本信息

批准号：
276698709
负责人：
Professor Dr. Alexander Zipf
金额：
--
依托单位：
Professur für Geoinformatik / GIScience (GIS)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/276698709?language=en
关键词：
agent based quality aware integration

项目摘要

Web-based social networks are now a significant social phenomenon. The user-generated data produced through them, including the location-based data, represents an important economic asset. Most of the spatial data being generated consists in points-of-interest (POIs). While POIs generally contain point geometries, they also include rich semantic information. However, as of today, we lack knowledge about the spatial data generated through these networks, their characteristics, quality and potential usage. Some studies deal with crowdsouring projects, especially OpenStreetMap (OSM). Still, there has been so far little focus on spatial data extracted from social networks. Preliminary investigations show that the different networks have complementary content. Therefore, methods for the fusion of spatial data extracted from geosocial networks are needed to enable the integrated use of the data, whereby the richness and quality of the resulting data could be be increased. Therefore, in the proposed project, we will develop methods for evaluating the quality and methods for integration of user-generated spatial data from different geosocial networks. In contrast with conventional data sources, the quality of the data extracted from geosocial networks is characterized by a high spatial heterogenity, while traditional data captured by authorities and companies usually are more homogeneous. Therefore, new methods to incorporate data quality into data integration must be developed. One key aspect that will be investigated to account for data quality, without having to systematically assess every data entry, is the contributors profile and behavior. Studies have demonstrated that some elements of a contributor s profile and behavior are linked to the quality of his or her contributions. Therefore, we will conduct our own study to detect the relation between data quality and contributors profiles. Then, the integration process will be modeled as an agent-based negotiation process based on Game Theory where agents representing contributors and their profile will negotiate the final representation of integrated data, in a way to maximize quality of resulting data. The method will be evaluated by comparing integrated data to commercial data, as official data from authorities usually does not include POI data with rich semantics. In summary, the main project s outcomes and contributions include new methods for the evaluation of user-generated spatial data from geo-social networks, keys findings concerning the relation between contributors profiles and data quality, as well as new methods for integration of these heterogeneous data sources using agent-based approaches. Since the quality of the different data sources is constantly changing in space and time, the focus is on the development of suitable methods so that the quality investigations, and the integration process can be repeated anytime.

基于Web的社交网络现在是一种重要的社会现象。通过它们产生的用户生成的数据，包括基于位置的数据，是一项重要的经济资产。生成的大多数空间数据都包含在兴趣点（POI）中。虽然POI通常包含点几何图形，但它们还包含丰富的语义信息。然而，到目前为止，我们对通过这些网络生成的空间数据、其特点、质量和潜在用途缺乏了解。一些研究涉及众包项目，特别是OpenStreetMap（OSM）。尽管如此，迄今为止，人们对从社交网络中提取的空间数据关注甚少。初步调查表明，不同的网络有互补的内容。因此，需要有从地理社会网络中提取的空间数据的融合方法，以便能够综合利用这些数据，从而提高所产生数据的丰富性和质量。因此，在拟议的项目中，我们将开发质量评估方法和整合来自不同地理社会网络的用户生成的空间数据的方法。与传统的数据来源相比，从地理社会网络中提取的数据的质量具有高度的空间异质性，而当局和公司获取的传统数据通常更为同质。因此，必须开发将数据质量纳入数据集成的新方法。将被调查以说明数据质量的一个关键方面是贡献者的个人资料和行为，而不必系统地评估每个数据条目。研究表明，贡献者的个人资料和行为的一些要素与他或她的贡献质量有关。因此，我们将进行自己的研究，以检测数据质量和贡献者配置文件之间的关系。然后，集成过程将被建模为基于博弈论的基于代理的协商过程，其中代表贡献者及其配置文件的代理将协商集成数据的最终表示，以最大限度地提高结果数据的质量。该方法将通过比较综合数据与商业数据进行评估，因为来自当局的官方数据通常不包括具有丰富语义的POI数据。总之，主要项目的成果和贡献包括评估地理社会网络中用户生成的空间数据的新方法，有关贡献者配置文件和数据质量之间关系的关键发现，以及使用基于代理的方法集成这些异构数据源的新方法。由于不同数据源的质量在空间和时间上不断变化，因此重点是开发合适的方法，以便随时重复质量调查和整合过程。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Coupling maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists

将最大熵建模与地理标记的社交媒体数据相结合，以确定游客的地理分布

DOI：
10.1080/13658816.2018.1458989
发表时间：
2018-04
期刊：
International Journal of Geographical Information Science
影响因子：
5.7
作者：
Yan Yingwei;Kuo Chiao-Ling;Feng Chen-Chieh;Huang Wei;Fan Hongchao;Zipf Alex;er
通讯作者：
er

Graph-Based Matching of Points-of-Interest from Collaborative Geo-Datasets