关键词: 敦煌壁画, 关联数据, 多粒度, 语义相似度, 实体相似度

Abstract: [Purpose/significance] With the developing of cultural heritage digitization and humanities computing paradigm, the demand of cultural heritage data resources from scholars in the field of humanities have increasingly highlighted when participating in digital humanities research. The semantic integration and interoperability of multi-source and heterogeneous cultural heritage information resources has become a key issue in the construction of digital humanities data infrastructure nowadays, and the effective method of entity semantic similarity calculation has became an important means to achieve this goal.[Method/process] Based on the analysis of the ontology model and data framework of Dunhuang Mural Thesaurus Linked Data, this paper proposed an entity semantic similarity calculation method based on the integration of multi granularity matching and weighted calculate, and selected "Feitian" related entities in the dataset as the experimental object to compare the effects of the method proposed in this paper with current methods base on attribute characteristic or edit distance in semantic similarity calculation.[Result/conclusion] The experimental results show that, compareing with the other methods, the entity semantic similarity calculation method based on multi-granularity matching can better adapt to the content and structural characteristics of Dunhuang Mural Thesaurus Linked Data, and has better performance in the accuracy of calculation. Thus this paper has introduced another feasible idea for promoting the data interconnection and knowledge sharing of heterogeneous human information resources under the background of digital humanities.

Key words: Dunhuang murals, linked data, multi-granularity, semantic similarity, entity similarity