KNOWLEDGE GRAPH ENABLED REPRESENTATION AND EXPLORATION FOR URBAN HISTORICAL BUILDINGS: A CASE STUDY IN BEIJING, CHINA

Abstract. Urban Historical Buildings (UHBs) preserve the past and memory of a city. Collecting and managing UHB knowledge efficiently is of vital importance to protect local culture heritages and meet the demands of sustainable development. However, UHB knowledge is commonly hidden in the texts from different sources, making it hard to access and manage by general methods efficiently. Meanwhile, domain agnostic knowledge graphs are challenging to express the rich semantic and multi-hop relationships among UHB knowledge. To address the above problems, we proposed a general framework for the extraction and management of the key knowledge from free texts about urban historical buildings. In this study, we attempted to build an UHB knowledge graph from free texts obtained from Internet. Firstly, we designed the UHB domain ontology to regulate the knowledge of urban historical building. Next, the structured knowledge was extracted from web text with Natural Language Processing (NLP) technologies. Finally, we built the UHB knowledge base and developed a Beijing UHB knowledge graph. Furthermore, we demonstrated knowledge retrieval and visualization based on UHB knowledge graph. Our experiment shows that mining UHB knowledge from free text is feasible and important for urban historical building conservation efforts.