Patent Trend Analysis through Text Clustering based on K-Means Algorithm

Analyzing the trend of patents is an important research topic. In this paper, we study patent trends from the perspective of text clustering. More specifically, we first construct vector space for patent document based on TF-IDF model, then use K-Means algorithm to carry out the text clustering. The result of the text clustering can be visualized in various ways such as ECharts diagrams. Moreover, we develop a patent trend analysis system based on Web form to demonstrate relative functions. The experimental results show that our system provides very intuitive and valuable patent trend information which help people analyze and understand patents trend.