Patent Landscaping

Patent landscaping involves identifying patents relevant to a specific technology area, a crucial task for intellectual property management that is traditionally time-consuming and expensive. Current research focuses on automating this process using machine learning, particularly neural networks and large language models, often incorporating techniques like graph-based knowledge retrieval and recommender systems to improve accuracy and efficiency, even with limited training data. These advancements aim to streamline patent analysis, improve the speed and quality of patent responses to office actions, and ultimately enhance the efficiency and effectiveness of intellectual property management for individuals and organizations.