Volume 14 Number 7 (Jul. 2019)
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JCP 2019 Vol.14(7): 479-496 ISSN: 1796-203X
doi: 10.17706/jcp.14.7.479-496

Patent Abstract Analysis on Chinese Big Data Based on A Filter-Refinement Scheme

Zongbao Yang, Shaohong Zhang, Jianyu Liu, Zhiqian Zhang, Xiaofei Xing, Ying Gao
Department of Computer Science, GuangZhou University, Guangzhou, P.R. China.
Abstract—Great attention has been paid to big data technologies by both industry and academia in recent years. Patent analysis is widely viewed as an important tool for tracking these technologies. However, there are some challenges when searching patents in practice, especially in the coverage of research results. Most patent analysis methods use keywords to search for information. However, big data techniques involve in many applications, and different patent applicants make various subjective decisions in the selection of keywords. Considering this problem, we proposed a new, more precise method for big data patent analysis based on a novel filter-refinement scheme. We compared our method with other keyword extracted methods, including SegPhrase, C-value, and Word2vec, etc. The experimental results show that the phrases extracted by the filter-refinement scheme outperformed the competitors on various measures and most of these phrases have a high quality. By applying our results to the analysis of domestic big data technologies in China, we found that there is greater development in industry than in academia; Huawei has the largest number of patent applications. In addition, the development of big data technologies in China is unbalanced, with the development level of the eastern regions significantly outperforming that of the western regions.

Index Terms—Big data patents, filter-refinement scheme, patent analysis, abstract analysis.

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Cite: Zongbao Yang, Shaohong Zhang, Jianyu Liu, Zhiqian Zhang, Xiaofei Xing, Ying Gao, "Patent Abstract Analysis on Chinese Big Data Based on A Filter-Refinement Scheme," Journal of Computers vol. 14, no. 7, pp. 479-496, 2019.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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