Topical Prescriptive Analytics System for Automatic Recommendation of Convergence Technology
This study applies text mining in scientific articles for discovery of interdisciplinary convergence technology between biotechnology (BT) and information and communication technology (ICT). For in-depth interpretation of the technologies without domain experts’ review, a topic modeling method, Late...
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Published in | Biotechnology and bioprocess engineering Vol. 24; no. 6; pp. 893 - 906 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Seoul
The Korean Society for Biotechnology and Bioengineering
01.12.2019
Springer Nature B.V 한국생물공학회 |
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Abstract | This study applies text mining in scientific articles for discovery of interdisciplinary convergence technology between biotechnology (BT) and information and communication technology (ICT). For in-depth interpretation of the technologies without domain experts’ review, a topic modeling method, Latent Dirichlet allocation (LDA), was used to propose an automatic recommendation system. We also applied prescriptive analytics with an option for users to select appropriate recommendation process of items. Our findings are as follows. First, LDA was efficient to facilitate the analysis of a large collection of documents by decreasing the dimension of the data. Second, the automatic recommendation method with various selectable options that could overcome limitations from that domain experts review the entire set of numerous topics. Finally, as a result of investigation of the final convergence technology candidates, it was proved that the system we propose here is more cost/time-effective compared to a method of reviewing all of the topic associations. Overall, a new methodology to support experts’ final decision by LDAand prescriptive analytics-based automatic recommendation system was successfully developed to discover convergence technologies between BT and ICT, which was also proved by several examples of applications. |
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AbstractList | This study applies text mining in scientific articles for discovery of interdisciplinary convergence technology between biotechnology (BT) and information and communication technology (ICT). For in-depth interpretation of the technologies without domain experts’ review, a topic modeling method, Latent Dirichlet allocation (LDA), was used to propose an automatic recommendation system. We also applied prescriptive analytics with an option for users to select appropriate recommendation process of items. Our findings are as follows. First, LDA was efficient to facilitate the analysis of a large collection of documents by decreasing the dimension of the data. Second, the automatic recommendation method with various selectable options that could overcome limitations from that domain experts review the entire set of numerous topics. Finally, as a result of investigation of the final convergence technology candidates, it was proved that the system we propose here is more cost/time-effective compared to a method of reviewing all of the topic associations. Overall, a new methodology to support experts’ final decision by LDAand prescriptive analytics-based automatic recommendation system was successfully developed to discover convergence technologies between BT and ICT, which was also proved by several examples of applications. This study applies text mining in scientific articles for discovery of interdisciplinary convergence technology between biotechnology (BT) and information and communication technology (ICT). For in-depth interpretation of the technologies without domain experts’ review, a topic modeling method, Latent Dirichlet allocation (LDA), was used to propose an automatic recommendation system. We also applied prescriptive analytics with an option for users to select appropriate recommendation process of items. Our findings are as follows. First, LDA was efficient to facilitate the analysis of a large collection of documents by decreasing the dimension of the data. Second, the automatic recommendation method with various selectable options that could overcome limitations from that domain experts review the entire set of numerous topics. Finally, as a result of investigation of the final convergence technology candidates, it was proved that the system we propose here is more cost/time-effective compared to a method of reviewing all of the topic associations. Overall, a new methodology to support experts’ final decision by LDAand prescriptive analytics-based automatic recommendation system was successfully developed to discover convergence technologies between BT and ICT, which was also proved by several examples of applications. KCI Citation Count: 0 |
Author | Jeong, Do-Heon Joo, Hwang-Soo |
Author_xml | – sequence: 1 givenname: Do-Heon surname: Jeong fullname: Jeong, Do-Heon organization: Department of Library and Information Science, Duksung Women’s University – sequence: 2 givenname: Hwang-Soo surname: Joo fullname: Joo, Hwang-Soo email: hwangsoojoo27@duksung.ac.kr organization: Department of Biotechnology, Duksung Women’s University |
BackLink | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002547209$$DAccess content in National Research Foundation of Korea (NRF) |
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Copyright | The Korean Society for Biotechnology and Bioengineering and Springer 2019 Biotechnology and Bioprocess Engineering is a copyright of Springer, (2019). All Rights Reserved. |
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Keywords | topic modeling Latent Dirichlet allocation prescriptive analytics convergence technology recommendation system |
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References_xml | – reference: ZDNet Korea, MSIT, Investing KRW 37.5 billion in the development of convergence technologies this year. http://www.zdnet.co.kr/view/?no=20190113104730. – reference: BertsimasDKallusNFrom predictive to prescriptive analyticsarXiv preprint2015 – reference: VulicIDe SmetWMoensM FCross-language information retrieval models based on latent topic models trained with document-aligned comparable corporaInf. Retr. Boston.20131633136810.1007/s10791-012-9200-5 – reference: JungS YAhnSNamK HLeeJ PLeeS JIn vivo measurements of blood flow in a rat using X-ray imaging techniqueInt. J. Cardiovasc. 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