用形式概念分析可视化标注数据，帮专家优化知识体系。
Assessing Semantic Annotation Activities with Formal Concept Analysis
- 通过形式概念分析构建概念格，展示标注中本体的使用情况。
- 专家可据此发现本体使用偏差，并提出针对性改进意见。
- 适用于需要优化标注流程与本体设计的知识工程团队。
本文提出一种基于形式概念分析（FCA）的语义标注评估方法。领域专家构建分类本体，标注者使用这些本体对数字资源进行标注。通过FCA，专家可获得以概念格形式呈现的可视化图表，直观展示本体在标注过程中的实际使用情况。这使专家能够指导标注者更有效地使用本体，并根据实际需求优化本体结构。文中以@note（一个用于文学文本协作标注的富互联网应用）为例，展示了该方法的实现，并通过案例研究和评估结果验证了其有效性。
原文摘要 · Abstract (English)
This paper describes an approach to assessing semantic annotation activities based on formal concept analysis (FCA). In this approach, annotators use taxonomical ontologies created by domain experts to annotate digital resources. Then, using FCA, domain experts are provided with concept lattices that graphically display how their ontologies were used during the semantic annotation process. In consequence, they can advise annotators on how to better use the ontologies, as well as how to refine them to better suit the needs of the semantic annotators. To illustrate the approach, we describe its implementation in @note, a Rich Internet Application (RIA) for the collaborative annotation of digitized literary texts, we exemplify its use with a case study, and we provide some evaluation results using the method.
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