Knowledge graph based on domain ontology and natural language processing technology for Chinese intangible cultural heritage. (October 2018)

• Record Type: Journal Article
• Authors: Dou, Jinhua; Qin, Jingyan; Jin, Zanxia; Li, Zhuang
• Is Part Of: Journal of visual languages & computing. Volume 48(2018)
• Page Start: 19
• Page End: 28
• Publication Date: 2018-10
• Subjects: Intangible cultural heritage -- The 24 solar terms -- Domain ontology -- Knowledge graph -- Natural language processing -- Deep learning; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2018.06.005
• Languages: English
• ISSNs: 1045-926X

Abstract

Highlights: We proposed knowledge graph for intangible cultural heritage(ICH) protection and dissemination. A method of building knowledge graph based on domain ontology and natural language processing technology for Intangible cultural heritage was explored. ICH ontology base was constructed according to the characteristics of the intangible cultural heritage with the help of intangible cultural heritage experts and knowledge engineer. Deep learning methods used in NLP technology were adopted to extract domain knowledge from massive ICH text data. ICH Knowledge base was constructed and ICH knowledge graph was developed to assist knowledge management and provide service to public. Abstract: Intangible cultural heritage (ICH) is a precious historical and cultural resource of a country. Protection and inheritance of ICH is important to the sustainable development of national culture. There are many different intangible cultural heritage items in China. With the development of information technology, ICH database resources were built by government departments or public cultural services institutions, but most databases were widely dispersed. Certain traditional database systems are disadvantageous to storage, management and analysis of massive data. At the same time, a large quantity of data has been produced, accompanied by digital intangible cultural heritage development. The public is unable to grasp key knowledge quickly because of the massive and fragmented nature of the data. To solve these problems, we proposed the intangible cultural heritage knowledge graph to assist knowledge management and provide a service to the public. ICH domain ontology was defined with the help of intangible cultural heritage experts and knowledge engineers to regulate the concept, attribute and relationship of ICH knowledge. In this study, massive ICH data were obtained, and domain knowledge was extracted from ICH text data using the Natural Language Processing (NLP) technology. A knowledge base based on domain ontology and instances for Chinese intangible cultural heritage was constructed, and the knowledge graph was developed. The pattern and characteristics behind the intangible cultural heritage were presented based on the ICH knowledge graph. The knowledge graph for ICH could foster support for organization, management and protection of the intangible cultural heritage knowledge. The public can also obtain the ICH knowledge quickly and discover the linked knowledge. The knowledge graph is helpful for the protection and inheritance of intangible cultural heritage.