Recent advancements in Artificial Intelligence (AI) and machine learning have demonstrated transformative capabilities across diverse domains. This progress extends to the field of patent analysis and innovation, where AI-based tools present opportunities to streamline and enhance important tasks in the patent cycle such as classification, retrieval, and valuation prediction. This not only accelerates the efficiency of patent researchers and applicants but also opens new avenues for technological innovation and discovery. Our survey provides a comprehensive summary of recent AI tools in patent analysis from more than 40 papers from 26 venues between 2017 and 2023. Unlike existing surveys, we include methods that work for patent image and text data. Furthermore, we introduce a novel taxonomy for the categorization based on the tasks in the patent life cycle as well as the specifics of the AI methods. This interdisciplinary survey aims to serve as a resource for researchers and practitioners who are working at the intersection of AI and patent analysis as well as the patent offices that are aiming to build efficient patent systems.

翻译：近年来，人工智能与机器学习领域的进展已在众多领域展现出变革性能力。这一进步延伸至专利分析与创新领域，基于人工智能的工具为优化和增强专利周期中的关键任务（如分类、检索与价值预测）提供了机遇。这不仅提升了专利研究人员与申请人的工作效率，也为技术创新与发现开辟了新途径。本综述全面总结了2017年至2023年间来自26个学术会议的40余篇论文中涉及专利分析的最新人工智能工具。与现有综述不同，本文涵盖了适用于专利图像与文本数据的方法。此外，我们提出了一种基于专利生命周期任务及人工智能方法细节的新型分类体系。这项跨学科综述旨在为人工智能与专利分析交叉领域的研究者、从业者，以及致力于构建高效专利体系的专利机构提供参考资源。