Knowledge extraction and strategic intelligence generation in the Yangtze River Protection Project

Abstract

The Yangtze River Protection Project adopts the EPC contracting mode, which is a large-scale project involving multi-stakeholders and a complex environment. The project faces complex synergistic relationships and difficult synergistic control challenges. Therefore, how to utilize the accumulated empirical knowledge to realize efficient and high-quality assisted collaborative control is the focus of attention of all parties. In order to effectively utilize the text knowledge, BERT-BiLSTM text classification model and RoBERTa-BiLSTM-CRF entity recognition model were proposed. Knowledge extraction experiments were designed relying on the Yichang two-network phase II project, and further knowledge extraction was carried out on the textual information of the Yangtze River Great Protection EPC project, and after entity alignment and structured storage, a replicable and scalable structured collaborative strategy library was finally formed. In addition, the entity recognition model is utilized to obtain the key entity information of the interrogative sentence, and the pending strategy set is obtained through matching retrieval. Finally, the strategy sentence fusion method is utilized to realize the semantic fusion of the pending strategy set based on sentence semantic relations, and the synergistic strategy is proposed to provide an important reference for the synergistic control of subsequent projects.

Keywords

Yangtze River Protection / knowledge extraction / collaborative management / intelligent strategy generation