A Novel Technology Intelligence Tool Based on Utility Mining

ALTUNTAŞ S., Sezer M.

IEEE Transactions on Engineering Management, vol.70, no.7, pp.2480-2492, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 70 Issue: 7
  • Publication Date: 2023
  • Doi Number: 10.1109/tem.2021.3101582
  • Journal Name: IEEE Transactions on Engineering Management
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Public Affairs Index, Civil Engineering Abstracts
  • Page Numbers: pp.2480-2492
  • Keywords: Patents, Tools, Databases, Companies, Market research, Itemsets, Text mining, Data mining, patent analysis, technological intelligence, utility mining, CROSS IMPACT ANALYSIS, PATENT ANALYSIS, INNOVATION, EVOLUTION
  • Yıldız Technical University Affiliated: Yes

Abstract

IEEEThe technological intelligence tools that companies need to achieve sustainable development in today's digital age are extremely limited. To fill this gap in the literature, a novel technology intelligence tool is developed in this article. The developed technology intelligence tool uses patent analysis and utility mining. It is based on the HUP-growth mining algorithm, which is one of the utility mining algorithms, to find the relationships between technologies. The developed technology intelligence tool has three contributions to the literature. First, the importance level of the technologies and the repetitions of each technology in a patent have been taken into consideration. Second, the existing studies in the literature cannot use a technology intelligence tool to explore the relationships between technologies. Third, the developed technology intelligence tool is more successful in finding hidden patterns among patent documents. A real-life case study of business method patents about electronic shopping is conducted to show how the developed technology intelligence tool works in practice. The Apriori algorithm is also used to compare the results obtained from on the HUP-growth mining algorithm. The results of this study show that companies can quickly and effectively find association among technologies under concern using the developed technology intelligence tool.