Table 1 A summary of previous studies on big data patenting activities
Study | Method of analysis | Technology | Scope | Patent + literature | Some of findings |
|---|---|---|---|---|---|
The current study | Bibliometric; social network analysis | Big data | Global | Patent and literature | Please check the result section of this paper |
[31] | Bibliometric, patent metrics, statistical analysis and other methods of related laws | Technical classification fields system of big data (9 classifications) | Global | Patents | Data mining, classification, big data, clustering, large data sets, machine learning, cluster analysis, algorithm, execution, and biological information are the ten big data fields with high occur frequency |
[30] | Word segmentation models on the basis of TF-IDF principle (text mining) | Chinese big data | China | Abstracts of patents | Development of big data patents in china after 2005; Patent applicants are mainly universities and enterprises with Huawei having the most qualities of patent applications; an unbalance situation in the development of big data technologies in China |
[32] | Text mining Social network analysis | European big data marketing | Europe | Patents | Patents are strongly connected so the sub- technologies of big data are depended to each other The top-ranked keywords are also image, layout, and object |
[33] | Tech mining | To measure “hot topics” in industry with regard to big data | Unspecified | Patents and publication | There is little co-occurrence among leading big data institutions The main topics in big data fields are business intelligence, cloud-based services, customer experience, social media, and healthcare and web services |