Study on Patent Entity Extraction Based on Improved Bert Algorithms—A Case Study of Graphene

The entity relation extraction is the key part to estimate the novelty of patents. The traditional entity relation extraction is the series system, but this style has major dwawbacks. The paper studies the evolution of entity relation extraction using two improved BERT algorithms. One is the method combining traditional Chinese features with syntactic semantic features, and the other is the method combining attention mechanism with syntactic semantic features. The extensive computational experiments and the preparation technology of the graphene show that the two algorithms can improve the analysis efficiency for the contents of the patents and reveal the dynamic evolution process of the technology of the graphene firm.