基于关联数据的数字博物馆语义融合研究与实现

发布时间：2018-05-08 20:13

本文选题：关联数据 + 语义网　；参考：《北京化工大学》2014年硕士论文

【摘要】：伴随网络信息技术的持续发展,世界范围内数字博物馆建设也保持着蓬勃发展的良好势头。而博物馆长久以来存在的各自为政的管理模式,给博物馆领域相关数据资源实现对外开放分享和资源整合带来了挑战。关联数据作为语义网技术的研究分支,为网络上发布和整合相关信息资源提供了一种有效手段。但是当前的关联数据在语义融合方面的研究仍存在关联链接的构建严重不足、关联类型有限、关联链接发布质量缺乏有效的控制机制等问题,因此开展基于关联数据的数字博物馆语义融合研究具有一定的理论意义和实践价值。本文从当前博物馆领域数据信息共享中存在的问题出发,对基于关联数据技术的语义融合进行了相关研究和实践。首先,本文在进行关联数据技术体系和基于关联数据的语义融合策略的理论研究的基础上,给出了一个基于关联数据的语义融合方法和适用模型。基于关联数据的语义融合方法通过关联性检测、概念特征模型获取、知识发现与关联构建等过程,旨在关联数据集间构建正确率较高的语义关联,并提供用户界面支持关联链接的质量审查以保证关联数据的发布质量。基于关联数据的语义融合模型分为数据层、领域本体层、元数据语义化层和应用服务层,其中元数据语义化又分为初始语义化和语义扩展两个子层。其次,开发了一个基于关联数据的数字博物馆语义融合平台,该平台分为领域资源层、语义融合层、关联数据网络层和应用服务层四个层次,目标是通过语义融合的方式对博物馆领域及其相关数据资源予以关联和整合。最后,通过实验分别对本文给出的方法和模型框架进行有效性验证和语义融合效果评价。实验表明,本文给出的基于关联数据的语义融合方法可以在博物馆数据集和外部数据集间构建七种语义关联,通过平台可视化界能够面对相关信息进行关联访问,具有较好的语义融合效果。
[Abstract]:With the continuous development of network information technology, the construction of digital museum in the world also keeps a good momentum of vigorous development. For a long time, the museum has its own management mode, which brings challenges to the opening up and integration of the related data resources in the museum field. As a branch of semantic Web technology, relational data provides an effective means to publish and integrate related information resources on the web. However, there are still some problems in the research of semantic fusion of association data, such as the construction of association link, the limited association type, the lack of effective control mechanism for the quality of association link publication, and so on. Therefore, the research on semantic fusion of digital museum based on associated data has certain theoretical significance and practical value. Based on the problems existing in the information sharing in the museum domain, this paper studies and practices the semantic fusion based on the association data technology. Firstly, on the basis of the theoretical research on the technology system of association data and the strategy of semantic fusion based on associated data, a semantic fusion method based on associated data and a suitable model are presented in this paper. The semantic fusion method based on association data is designed to construct semantic association with high accuracy among association data sets through the process of association detection, concept feature model acquisition, knowledge discovery and association construction. A user interface is provided to support quality review of associated links to ensure the quality of associated data release. The semantic fusion model based on association data is divided into data layer, domain ontology layer, metadata semantic layer and application service layer, in which metadata semantics is divided into two sub-layers: initial semantic layer and semantic extension layer. Secondly, a digital museum semantic fusion platform based on associated data is developed. The platform is divided into four layers: domain resource layer, semantic fusion layer, associated data network layer and application service layer. The goal is to associate and integrate the museum domain and its related data resources through semantic fusion. Finally, the validity of the proposed method and the model framework are validated and the semantic fusion effect is evaluated by experiments. Experiments show that the semantic fusion method based on association data can construct seven kinds of semantic associations between museum data set and external data set. It has good semantic fusion effect.
【学位授予单位】：北京化工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.4

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