Design and implementation strategy of social responsibility sharing mechanism of existing building energy-saving renovation subject

It is the key to promote the development of energy-saving renovation market of existing buildings to share the social responsibility of the subject of energy-saving renovation of existing buildings.This paper analyzes the principle and implementation conditions of social responsibility sharing of existing building energy-saving renovation subject,discusses the mode selection and contract design of social responsibility sharing of existing building energy-saving renovation subject,analyzes the implementation mechanism of social responsibility sharing of existing building energy-saving renovation subject from the perspectives of information platform architecture,shared process design and shared system construction.And this paper puts forward the implementation strategy of sharing the social responsibility of the subject of the existing building energy-saving renovation from the aspects of stabilizing the subject’s cooperative relationship,creating a good responsibility environment and improving the responsibility performance laws and regulations.

Targeted BERT Pre-training and Fine-Tuning Approach for Entity Relation Extraction

Entity relation extraction(ERE)is an important task in the field of information extraction.With the wide application of pre-training language model(PLM)in natural language processing(NLP),using PLM has become a brand new research direction of ERE.In this paper,BERT is used to extracting entityrelations,and a separated pipeline architecture is proposed.ERE was decomposed into entity-relation classification sub-task and entity-pair annotation sub-task.Both sub-tasks conduct the pre-training and fine-tuning independently.Combining dynamic and static masking,newVerb-MLM and Entity-MLM BERT pre-training tasks were put forward to enhance the correlation between BERT pre-training and TargetedNLPdownstream task-ERE.Inter-layer sharing attentionmechanismwas added to the model,sharing the attention parameters according to the similarity of the attention matrix.Contrast experiment on the SemEavl 2010 Task8 dataset demonstrates that the new MLM task and inter-layer sharing attention mechanism improve the performance of BERT on the entity relation extraction effectively.