[目的/意义] 金融科技在信息和数据时代发展迅速，专利数目不断增长，同时金融科技的领域交叉和边界模糊等特性，也提升了其专利分析的难度。因此需要构建适合的识别与分类方法，从而准确高效地处理持续增长的大体量数据。[方法/过程] 首先依据金融科技的内涵和功能，梳理其包含的创新类别，厘清金融科技专利的范围和边界；随后使用机器学习算法，结合文本过滤、人工判读，构建金融科技专利识别与分类的方法流程。[结果/结论] 提出一种基于机器学习算法的专利识别与分类流程，能够较为准确高效地识别金融科技专利并进行分类，并通过分析所得的金融科技专利分类数据，总结当前金融科技的发展现状。
[Purpose/significance] FinTech has developed rapidly in the information and data era, and the number of patents has continued to increase. At the same time, its field crossover and blurred borders characteristics have also increased the difficulty of patent analysis. Therefore, it is necessary to construct a suitable identification and classification method, so as to accurately and efficiently process the continuously growing large volume data. [Method/process] This paper firstly sorted out the innovation categories based on the connotation and function of FinTech, and thus clarified the scope and boundaries of FinTech patents. Then, it constructed a FinTech patent recognition and classification model based on machine learning algorithms, combining text filtering and manual interpretation. [Result/conclusion] This paper proposes a patent recognition and classification process, based on machine learning algorithms, which is more accurately and efficiently. By analyzing the obtained FinTech patent classification data, the research also summarizes the current FinTech development status.
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