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Exploring the intellectual structure of cloud patents using non-exhaustive overlaps

Author

Listed:
  • Jia-Yen Huang

    (National Chin-Yi University of Technology)

  • Rong-Chang Chen

    (National Taichung University of Science and Technology
    National Taichung University of Science and Technology)

Abstract

Utilizing advanced information technology to identify the intellectual structure of patents is important for the fast-emerging cloud computing industry; however, related literature is limited. Because the existing three categories of cloud computing business mode are partially overlapped, the customary SPI model as a basis for patent analysis is unable to grasp the development status of cloud computing correctly. The aims of this study are to obtain clustering of cloud patent with overlapping claims and to identify the intellectual structure of different research themes in the development of cloud computing. This study first proposes an ontology-based compound retrieval policy to retrieve three non-overlapped cloud patents. We then propose a new overlapping cluster algorithm using the patents with the highest degree centralities as the initial central points for clustering, and utilizing the Taguchi and technique for order preference by similarity to ideal solution methods for integrating the clustering quality-related indices. Based on the database of the three overlapped clusters of cloud computing patents, we propose a group technology-based co-word analysis, incorporating with the visual methods of social network analysis and multivariate analysis, to investigate the R&D themes in each service mode of cloud computing. Based on the analysis results, technologies related to computer-readable storage medium and computer program are of particular interest to the SaaS enterprises. The virtual machine technologies are the major development directions of PaaS enterprises, and virtual computing environment has gained many attentions from the IaaS enterprises. The proposed method for exploring the intellectual structure, as well as the analyzed results for unveiling the development status of cloud computing and the co-opetition relationship between companies, can provide valuable references for cloud-related companies to make their R&D management strategy.

Suggested Citation

  • Jia-Yen Huang & Rong-Chang Chen, 2019. "Exploring the intellectual structure of cloud patents using non-exhaustive overlaps," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 739-769, November.
    • Handle: RePEc:spr:scient:v:121:y:2019:i:2:d:10.1007_s11192-019-03219-4
    DOI: 10.1007/s11192-019-03219-4
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    References listed on IDEAS

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    1. Chang-Ping Hu & Ji-Ming Hu & Sheng-Li Deng & Yong Liu, 2013. "A co-word analysis of library and information science in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 369-382, November.
    2. Chen, Yen-Liang & Hu, Hui-Ling, 2006. "An overlapping cluster algorithm to provide non-exhaustive clustering," European Journal of Operational Research, Elsevier, vol. 173(3), pages 762-780, September.
    3. Ding, Ying, 2011. "Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks," Journal of Informetrics, Elsevier, vol. 5(1), pages 187-203.
    4. Gao-Yong Liu & Ji-Ming Hu & Hui-Ling Wang, 2012. "A co-word analysis of digital library field in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 203-217, April.
    5. Qian-Jin Zong & Hong-Zhou Shen & Qin-Jian Yuan & Xiao-Wei Hu & Zhi-Ping Hou & Shun-Guo Deng, 2013. "Doctoral dissertations of Library and Information Science in China: A co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 781-799, February.
    6. Jia-Yen Huang & Hung-Tu Hsu, 2017. "Technology–function matrix based network analysis of cloud computing," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 17-44, October.
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