Technology Opportunity Analysis: Combining SAO Networks and Link Prediction

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 r...

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Veröffentlicht in:IEEE transactions on engineering management Jg. 68; H. 5; S. 1288 - 1298
Hauptverfasser: Han, Xiaotong, Zhu, Donghua, Wang, Xuefeng, Li, Jia, Qiao, Yali
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Cancer
Link prediction
Melanoma
Network analysis
New technology
Prediction algorithms
Semantic analysis
Semantics
skin malignant melanoma
subject–action–object (SAO) network
Tech mining
Technological innovation
Technology assessment
technology opportunity analysis
Text mining
ISSN:0018-9391, 1558-0040
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Zusammenfassung: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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ISSN:0018-9391
1558-0040
DOI:10.1109/TEM.2019.2939175