Research And Implementation Of Question Answering System For Construction Codes Based On Deep Learning

China has formed a relatively complete building standard system,which can regulate the design,construction,acceptance and other stages of construction projects.At present,construction practitioners mainly look for construction articles by reading,or search for construction codes from search engines,but traditional search engines cannot quickly and accurately allow users to obtain the answers they want.Therefore,it is necessary to provide construction practitioners with a professional system that can quickly,conveniently and accurately answer questions raised by users.This paper takes the construction engineering quality acceptance code as the data source,and proposes question answering system method for the construction engineering quality acceptance code.This system integrates the deep learning model of information retrieval and natural language processing.It mainly does the following work:1.According to the professional characteristics of construction engineering specification documents,a knowledge base of construction engineering quality acceptance codes is constructed.This is the first attempt of the construction engineering specification documents in the research of question answering system.2.In order to better build a question answering system for the construction field,the BERT model is used in the question answering system for the construction engineering quality acceptance code,and the construction of the question answering system based on the BERT model and the traditional TF-IDF algorithm is combined with the traditional template.The driven question answering system is different.This article focuses on text documents and small corpora with low expandability.The proposed method has strong feature representation and learning capabilities,which can solve the construction acceptance problems raised by users.3.Combining the BERT model with the traditional TF-IDF algorithm,an automatic question answering system for construction engineering quality acceptance code is realized.At the same time,a prototype system chat robot was developed,and the chat robot was connected to the We Chat public account,so that construction practitioners can learn the relevant knowledge in the construction field conveniently and efficiently.According to the system test results,the effect of the question answering system proposed in this paper on the quality acceptance codes for construction engineering based on deep learning meets the requirements.As the first attempt of the engineering code file on the question answering system,this system reduces the dependence on labor,has a high degree of automation,and has strong versatility,which is worthy of further research.