文化遗产数字图像的表达与展示:一种语义丰富的方法

IF 0.6 4区 管理学 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE
Xu Tan, Xiaoxi Luo, Xiaoguang Wang, Hongyu Wang, Xilong Hou
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引用次数: 3

摘要

文化遗产数字图像包含着丰富的语义信息。然而,今天的语义表示的CH图像未能充分揭示内容实体和上下文在这些重要的代理。本文借鉴图像研究和数字人文学科领域,提出了CH数字图像语义丰富的系统方法和技术路线。该方法系统地应用了一系列步骤,包括:语义标注、基于实体的浓缩、建立内部关系、以事件为中心的浓缩、定义属性之间的层次关系、文本标注以及命名实体识别,最终提供细粒度上下文语义内容披露。最后,以敦煌典型壁画《五台山图》为例,构建了一种基于CH的数字图像可视化展示平台,验证了所提出的语义丰富方法语义表示的可行性和优势。本研究证明,语义富集为在细粒度层面上暴露内容,建立以CH数字图像内容为中心的丰富语义网络提供了一个有前景的新模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Representation and Display of Digital Images of Cultural Heritage: A Semantic Enrichment Approach
Digital images of cultural heritage (CH) contain rich semantic information. However, today’s semantic representations of CH images fail to fully reveal the content entities and context within these vital surrogates. This paper draws on the fields of image research and digital humanities to propose a systematic methodology and a technical route for semantic enrichment of CH digital images. This new methodology systematically applies a series of procedures including: semantic annotation, entity-based enrichment, establishing internal relations, event-centric enrichment, defining hierarchy relations between properties text annotation, and finally, named entity recognition in order to ultimately provide fine-grained contextual semantic content disclosure. The feasibility and advantages of the proposed semantic enrichment methods for semantic representation are demonstrated via a visual display platform for digital images of CH built to represent the Wutai Mountain Map, a typical Dunhuang mural. This study proves that semantic enrichment offers a promising new model for exposing content at a fine-grained level, and establishing a rich semantic network centered on the content of digital images of CH.
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来源期刊
Knowledge Organization
Knowledge Organization INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
1.40
自引率
28.60%
发文量
7
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