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| Patent Screening of Core Documents and Impact of Patent Technology Subject Identification |
| Li Shuying, Zhang Xin, Xu Yi, Xu Haiyu, Zhang Xian, Zhu Yuexian |
| Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041 |
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Abstract Technical feature words are considered to play a key role in technology networks. This study compares the efficiency of technical feature words extracted from the core patent dataset with those of the whole dataset and discusses the impact of core patent screening on the identification of technology features based on citation networks. This study applies the patent citation intensity indicator and citation time lag into patent screening of core patent documents in two steps. Furthermore, the differences between core documents and whole documents were identified in terms of word cloud, word frequency coverage, threshold selection, and division of technical topics. An empirical analysis on the biomedicine applications of graphene indicates that the feature words extracted from the core patent dataset help increase recognition efficiency and accuracy, and the technology co-classification network generated from the core dataset is more focused than the one generated from the whole network; this effectively simplifies data cleaning and also aids topic identification and expert interpretation.
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Received: 17 October 2018
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