Abstract
With the growing awareness of applying advanced technologies in hardware, software, and their integration for industrial applications, such as intelligent manufacturing (Industry 4.0), there are increasing demands in fast securing intellectual properties (IPs), to commercially protect competitive products and innovations. In order to allowing machine to learn rapid growing amount of IP documents, such as patent documents, Natural Language Processing (NLP) and Deep Learning (DL) algorithms should be deployed for their context e-discovery. The means to explain the related patent documents in a short summary remains a significant challenge. In this research, we develop an intelligent patent summarization system based on artificial intelligence (AI) approaches that include Recurrent Neural Network (RNN), Word Embedding, and Attention Mechanisms. The aim of this system is to automatically summarize multi-lingual patents in Chinese and English. The AI-based solution for summarization is used to capture the key technical keywords, popular terminologies. The ROUGE- Precision ratio and recall ratio are used to evaluate the accuracy and consistency of the output pf summarization.