Knowledge graph construction method based on improved BERT model

Abstract

The invention discloses a knowledge graph construction method based on an improved BERT model, and the method comprises the steps: obtaining multi-source heterogeneous data, and storing the obtained multi-source heterogeneous data to a big data platform; carrying out knowledge modeling on the acquired multi-source heterogeneous data based on the ontology; acquiring a knowledge on the basis of a BERT-BiGRU-CRF model; performing entity fusion and attribute fusion on the obtained heterogeneous data sources based on knowledge fusion of word vectors; and performing knowledge storage by adopting a graphic database. The enterprise knowledge graph is adopted to break through a traditional calculation mode, internal and external information and data in the field of enterprise operation management are deeply integrated, early warning potential risks can be more effectively mined in the later period, enterprise operation management efficiency is improved, and improvement of accuracy of subsequententerprise operation management risk intelligent diagnosis is facilitated.

Description

technical field [0001] The invention belongs to the technical field of knowledge graphs, in particular to the field of enterprise management, and in particular to a method for constructing knowledge graphs based on an improved BERT model. Background technique [0002] Knowledge graph is a new generation of semantic-based structured information organization method, which was proposed by Google in 2012. Different from the existing mainstream relational data model, the knowledge map focuses on describing the concepts and their relationships in the physical world in symbolic form. -Value pairs, entities are connected to each other through relationships to form a networked knowledge structure. At present, there are many methods for short text similarity calculation at home and abroad. For example, Professor Zhang Qi of Fudan University proposed a method of sentence similarity measurement, considering uni-gram, bi-gram and tri-gram in the sentence. These similarity results are c...

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Problems solved by technology

On the other hand, due to the complex causes of internal management risks and the difficulty in risk analysis and identification, enterprises currently rely mainly on expert experience, and risk analysis is mainly limited to various departments and systems, which cannot meet the high-quality development needs of enterprises

Based on the operation and management data from different sources within the enterprise, such as industrial and material management data and complaint samples, legal affairs, corporate culture and clean government construction data, use deep learning and other technologies to build a multi-subject and multi-dimensional knowledge map to intelligently identify internal risk factors of the enterprise , risk indicators, risk characteristics and risk causes will be a complex project

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