Automatic Summarization Generation Technology of Network Document Based on Knowledge Graph

The Internet has become one of the important channels for users to access to information and knowledge. It is crucial that how to acquire key content accurately and effectively in the events from huge amount of network information. This paper proposes an algorithm for automatic generation of network document summaries based on knowledge graph and TextRank algorithm which can solve the problem of information overload and resource trek effectively. We run the system in the field of big data application in packaging engineering. The experimental results show that the proposed method KG-TextRank extracts network document summaries more accurately, and automatically generates more readable and coherent natural language text. Therefore, it can help people access information and knowledge more effectively.