(2024). Automated Patent Landscaping Using Deep Learning, Proceedings of the 5th Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2024), in: Hidir Aras et al. (
Patent Landscaping is a valuable instrument for many stakeholders, such as patent examiners, company decision-makers, researchers, and policymakers. They use this method to analyze the state-of-the-art, compare organizations’ patenting activities, assess entire industries, or identify gaps in internal R&D activities. However, analyzing vast amounts of patent documents and aggregating and visualizing information is cumbersome and complex. The paper presents an innovative approach to automated patent landscaping by combining natural language processing models with approximate nearest neighbor search, dimensionality reduction, and clustering methods. This entire approach only uses the textual content of the underlying patents and does not use any additional meta-data, such as technology classes or citations.
Event: 5th Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2024), Washington, D.C., 2024-07-28
