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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (12): 63-73    DOI: 10.11925/infotech.2096-3467.2017.0820
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Hierarchical Classification Model for Invention Patents
Dongsheng Zhai,Dengjin Hu(),Jie Zhang,Xijun He,He Liu
School of Economics and Management, Beijing University of Technology, Beijing 100124, China
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[Objective] This paper proposes a new model to process patent information based on machine learning classification algorithm, aiming to determine the level of invention. [Methods] First, we extracted the technology feature words from the patent texts. Then, we constructed the patent technology feature vector with an algorithm trained by Word2Vec. Third, we calculated patent text indicators and backward references to build the training set. Finally, we constructed the new model with machine learning classification algorithm. [Results] We retrieved patents in the field of speech recognition technology with the proposed model. We found that the proportion of advanced level to entry level patents was around 1:4, which was in line with the actual situation. [Limitations] The WordNet dictionary will limit the results of extraction. [Conclusions] The proposed model could effectively identify the advanced patents and recommend them to the business owners.

Key wordsPatent Invention Level      Technical Feature Vector      Word Vector      Machine Learning     
Received: 15 August 2017      Published: 29 December 2017

Cite this article:

Dongsheng Zhai,Dengjin Hu,Jie Zhang,Xijun He,He Liu. Hierarchical Classification Model for Invention Patents. Data Analysis and Knowledge Discovery, 2017, 1(12): 63-73.

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