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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| Vydané v: | IEEE transactions on engineering management Ročník 68; číslo 5; s. 1288 - 1298 |
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| Médium: | Journal Article |
| Jazyk: | English |
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New York
IEEE
01.10.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0018-9391, 1558-0040 |
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| Abstract | 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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| AbstractList | 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. |
| Author | Qiao, Yali Wang, Xuefeng Zhu, Donghua Li, Jia Han, Xiaotong |
| Author_xml | – sequence: 1 givenname: Xiaotong orcidid: 0000-0003-2318-5207 surname: Han fullname: Han, Xiaotong email: 767013270@qq.com organization: School of Management and Economics, Beijing Institute of Technology, Beijing, China – sequence: 2 givenname: Donghua surname: Zhu fullname: Zhu, Donghua email: zhudh_bit@163.com organization: School of Management and Economics, Beijing Institute of Technology, Beijing, China – sequence: 3 givenname: Xuefeng orcidid: 0000-0002-4857-6944 surname: Wang fullname: Wang, Xuefeng email: wxf5122@bit.edu.cn organization: School of Management and Economics, Beijing Institute of Technology, Beijing, China – sequence: 4 givenname: Jia surname: Li fullname: Li, Jia email: 1107210296@qq.com organization: School of Management and Economics, Beijing Institute of Technology, Beijing, China – sequence: 5 givenname: Yali surname: Qiao fullname: Qiao, Yali email: qiaoyali_work@163.com organization: School of Management and Economics, Beijing Institute of Technology, Beijing, China |
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| SubjectTerms | 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 |
| Title | Technology Opportunity Analysis: Combining SAO Networks and Link Prediction |
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