The intelligent guidance and key knowledge matching method for engineering construction experience based on prompt learning

Abstract

Engineering construction is a typical knowledge-intensive field, where experiential knowledge is an important source of construction knowledge. Effectively acquiring construction experience is one of the key tasks for enterprises. However, such experiential knowledge is characterized by fragmentation and tacitness, making it difficult to collect and utilize. To address this, a method for intelligent guidance of construction experience and key knowledge matching is proposed. First, a prompt-based text classification technique is introduced to locate the content of construction experience knowledge by dividing expert experience texts into different thematic text blocks. Based on this, by analyzing the characteristics of construction experience texts and construction specification clauses, the study proposes a approach—regular expressions to construct rules. These rules are then utilized in matching analysis to align the elements of expert experiential knowledge, ultimately generating prompt information to guide experts toward further reflection and targeted responses. This method offers a new approach for the in-depth excavation and utilization of construction experience in engineering.

Keywords

municipal engineering / prompt learning / experience guidance / text classification / knowledge matching