Prefabricated construction (PC) plays a critical role in advancing the sustainable and high-quality transformation of the construction industry. Nevertheless, the fragmented and variable nature of technological innovations in PC complicates their acquisition, comprehension, and practical application, thereby hindering the process of innovation transformation. In response to these challenges, this study applies knowledge graph techniques to aggregate, correlate, and store knowledge pertaining to PC technological innovations. Specifically, using patent data from the past five years, and grounded in knowledge management and complex network theories, this study employs text mining, topic modeling, and association rule algorithms to perform clustering, evolutionary, and association analyses. The extracted entities and relationships obtained from the analyses are then stored in a Neo4j graph database for the construction and interactive visualization of a knowledge graph for PC technological innovation. According to the knowledge graph, a question-and-answer system framework is further proposed, providing practical application guidance. This research provides a comprehensive overview of the technological landscape, key nodes, and development trends in PC. It makes a meaningful contribution to knowledge management theory and complex network theory, advancing innovative applications in PC technology.
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