Research on Intelligent Patent Classification Scheme Based on Title Analysis
With the rapid increasing number of patents, it is becoming more significant but difficult to mine underlying information from huge patent data in database. By integrating Latent Dirichlet Allocation (LDA) topic mode with text mining algorithms, we propose two patent classification schemes: topic-based patent classification and title word-frequency-based patent classification, which can be applied in the areas of patent retrieval, patent evaluation and patent recommendation. The process and implementation methods of proposed schemes are discussed, and the examples to intelligently classify patent records in the area of railway transportation in international patent database are given, the results can adequately verify effectiveness of our proposed schemes.
KeywordsPatent classification Text mining Topic analysis LDA model Clustering algorithm Railway transportation
- 1.Liu, F., Ma, R.: Growth patterns of national innovation capacity: international comparison based on technology development path. Sci. Sci. Manag. S. & T. 34(4), 70–79 (2013)Google Scholar
- 2.Zhu, H.: Research on Several Core Techniques of Text Mining. Beijing Institute of Technology Press, Beijng (2017)Google Scholar
- 3.Li, B.: Machine Learning Practice & Application. Poster and Telecom Press, Beijing (2017)Google Scholar
- 4.Patent database of European Patent Office. https://worldwide.espacenet.com/classification
- 5.Yuan, M.: Foundation of Machine Learning-Principle, Algorithm & Practice. Tsinghua University Press, Beijing (2018)Google Scholar