众源地理信息的可信度计算模型与算法研究

众源地理信息的开放性与贡献者的非专业性导致众源地理数据质量参差不齐。尽管传统地理数据质量评价有一套较完善的体系，但难以适用于众源开放环境下的地理数据质量评价。探索一套适应众源数据的有效质量评价方法，是地理信息领域十分关注的重要问题。本项目拟针对这一国际学术前沿问题，开展基于众源地理信息可信度的质量评价机制研究：(1) 研究众源地理信息与专业地理信息在可信度计算模式上的互补性，系统地分析众源地理信息可信度的影响机理；(2) 应用地理目标修正与变更数据，探索研究贡献者多类隐式评价的原理和量化方法，构建基于隐式评价的众源信息志愿者综合信誉动态计算模型；(3) 研究地理目标与周边地物的相容度量化方法，提出融合基于志愿者信誉、目标相容度和目标自身质量等多类信任关系的众源地理信息可信度计算的综合模型。预期研究成果将深化众源地理信息可信度计算的理论基础，为众源信息的质量控制和筛选提供新的思路和理论依据。

Data quality of crowd-sourcing geographic information varies greatly because of its openness and unprofessional volunteers. Although there is a sophisticated mechanism for evaluating the quality of traditional geographic information, it cannot apply to the quality assessment of crowd-sourcing geographic information in such an open environment. It is really an important problem, which arrests the attention of the domain of geographic information science, to explore a suite of effective quality assessment to adapt to crowd-sourcing geographic information. Fortunately, the trustworthiness-based quality assessment mechanism is a feasible alternative. This project aims at this international academic frontiers and will research models and algorithms of trustworthiness computation for crowd-sourcing geographic information. First of all, after researching the complementariness of trustworthiness measurement between professional geographic information and the new environment, the influencing mechanism of trustworthiness of crowd-sourcing geographic object will be analyzed. Secondly, by means of exploring and investigating principle and computing method for implicit assessment of contributors by amendment and change information of geographic objects, a dynamic computation model of synthetic volunteer reputation based on implicit assessments among volunteers for crowd-sourcing geographic information will be proposed. At last, the conflict degree between geographic objects and their surrounding objects will be concentrated on. And a crowd-sourcing geographic information trustworthiness model integrating with volunteer reputation, quality of crowd-sourcing geographic information and conflicts of geographic objects will be come up. This study will deepen theory foundation of trustworthiness computation of crowd-sourcing geographic information and provide innovative ideas and theories for the quality control and screening of crowd-sourcing geographic information.