{'fraction_non_alphanumeric': 0.015486725663716814, 'fraction_numerical': 0.0, 'mean_word_length': 5.958974358974359, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Patent Network Analysis for Identifying Technological Evolution: A Case Study of China's Artificial Intelligence Technologies

Identifying technological evolution is a crucial way to assist in technology management. Since modern technology has become more and more complex and dynamic, general statistical techniques can hardly capture the underlying information of technological interconnection in the process of technology evolution. However, complex network analysis can be considered to be a powerful tool to investigate this issue. At the same time, patent documents containing rich information to indicate technological evolution in sequential time period can be a significant data source. This paper, based on the core terms derived from patent documents, constructs technological networks, to present the distribution of technologies. The comparison between the networks in sequential time periods can not only provide a way to understand technological evolution in detail, but also forecast technology opportunities, which can be used to help understand the development of selected technologies quickly and provide insights to research and development (R&D) plan and technological commercialization. A case study on exploring the evolution of China's artificial intelligence technologies is conducted to demonstrate the feasibility of this method.