Knowledge Management With Knowledge Graph Based On AEC Text

Architecture,Engineering & Construction(AEC)industry is typical knowledge & risk sensitive,and the process of engineering construction & management highly depends on mandatory documents such as national specifications,industry standards and internal regulations of the group,which brings great difficulties to many necessary tasks in engineering construction management,including project management regulations preparation,disclosure scheme review,construction report acceptance and so on.Because the knowledge involved in these tasks are more and more numerous and interrelated,and the specific compliance requirements are also more and more difficult to be mastered by human being due to the continuous development of AEC.On the other hand,it is considered significant to improve the Knowledge Management(KM)level of the AEC field,and there has been many works and researches based on AEC normaltive texts,as they contain a large amount of explicit knowledge related to AEC field.It is a feasible way to solve the typical problems above,and improve the efficiency and quality of engineering construction management.However,at present,the relevant research still faces two deficiencies: one is that the scale of data involved is very small,and the other one is that the characteristics involved are relatively simple.These two points lead to the lacks of universality and reliability in the current related research.In order to deal with the above problems,this study first collected a large scale of307 MB AEC specification text data.And then the hierarchy complexity degradation and feature analysis are carried out,to support the batch acquisition of structured information from the AEC text data.After that,this study combs the basic knowledge system of engineering construction management and defines the “meta knowledge object” of engineering construction management,based on which a large-scale knowledge graph with 200 thousand nodes and 2 million edges is built.The KG can be used to provide support for the fast retrieval of relevant knowledge objects and their semantic relationships.this study further discusses a complete KM flow with semantic knowledge retrieval,evaluation,understanding and application,with which two basic and valuable knowledge application is proposed: one is the engineering construction safety management regulations auto-complicance checking(ACC),and the other is the highly directional semantic safety knowledge question & answering(Q & A).Finally,the whole technical map and results and in this study is integrated to build the construction safety management KM platform,which realizes the complete flow of "feature → knowledge→ application → platform".The case study shows that the overall quality of the KG constructed by this research is good,and the ACC of engineering construction safety management regulations also obtains 63% F1 score,which means it can be apply on relevant practical work to a certain extent.In general,the technical map and corresponding data accumulation in this study improve the automation level of engineering construction management,and have great application prospects.