Research on Keyword-Based Element Extraction for Chinese Patent Retrieval

Patent retrieval is a critical step in patent analysis. Retrievable elements play a key role in constructing search queries and performing accurate searches, and most retrievable elements are created manually. However, the increment of patent applications each year has brought a huge burden on manual extraction of retrievable elements and patent examination, raising the urgent need of automated solutions. As keywords serve as an effective way of expressing retrievable elements in patent retrieval, we explore the automatic extraction of keyword-based retrievable elements from Chinese patent application texts in this study. We employ various keyword extraction methods, including large language model based methods, to identify retrievable elements within these texts. Our experimental results have shown that these methods can effectively extract keywords as retrievable elements from Chinese patent applications, which benefits to manual patent searching and patent examinations.