Journal
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
Volume 68, Issue 5, Pages 1288-1298Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEM.2019.2939175
Keywords
Link prediction; network analysis; skin malignant melanoma; subject-action-object (SAO) network; technology opportunity analysis
Categories
Funding
- General Program of National Natural Science Foundation of China [71774012, 71673024]
- Strategic Research Project of the Development Planning Bureau of the Chinese Academy of Science [GHJ-ZLZX-2019-42]
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Detecting early signs of technological changes is crucial for enterprise success, and SAO analysis can help identify future technology opportunities. The study shows that technology opportunities are likely to be found in potential connections between technologies.
Detecting the first signs of change in one's technological surroundings is a critical factor in the success of an enterprise, and technology opportunity analysis can be a crucial process in identifying those signs. However, the common keyword-based methods of analysis do not fully express the relationships between technologies. Subject-action-object (SAO) analysis offers a solution to this problem but, currently, these methods only consider the relationships that already exist. Yet, intuitively, technology opportunities are most likely to reside in potential connections. To test this notion, in this article we conduct a case study on malignant melanoma of the skin. First, we construct an SAO network of the titles and abstracts of medical documents, then use a link prediction algorithm to identify probable future links between unconnected nodes. These possible new technology combinations are further analyzed with a backtracking algorithm to reveal the most promising technology opportunities. Further analysis of the results combined with medical knowledge confirms the effectiveness of our method.
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