TY - JOUR
T1 - Exploration of Science and Technology Interaction
T2 - A Case Study on Taxol
AU - Suominen, Arho
AU - Ranaei, Samira
AU - Dedehayir, Ozgur
N1 - Funding Information:
Manuscript received November 12, 2018; revised January 14, 2019 and May 3, 2019; accepted June 11, 2019. Date of publication July 30, 2019; date of current version August 20, 2021. This work was supported by Academy of Finland (Modeling Science and Technology Systems Through Massive Data Collections) under Grant 288609. Review of this manuscript was arranged by Department Editor Dirk Meissner. (Corresponding author: Arho Suominen.) A. Suominen is with VTT Technical Research Centre of Finland, 02150 Espoo, Finland (e-mail: [email protected]).
Publisher Copyright:
© 1988-2012 IEEE.
PY - 2021/12
Y1 - 2021/12
N2 - Linkages between science and technology have been extensively studied using nonpatent literature citations or author-inventor matching. These methods suffer from limitations, such as the lack of citations to relevant documents or challenges with the disambiguation of author–inventor linkages. To mitigate these limitations, this paper uses Latent Dirichlet Allocation to create topic-based linkages between publications and patents based on the semantic content in the documents. The approach allows for the detection of topical overlap between patent and scientific publications, highlighting topical areas shared by research and application. Using a case study on “Taxol,” a cancer drug, with in total 26 475 documents retrieved from EuropePMC database the study illustrates the performance of the approach. The study offers qualitative and quantitative support that the approach is valuable in detecting patent and publication linkages.
AB - Linkages between science and technology have been extensively studied using nonpatent literature citations or author-inventor matching. These methods suffer from limitations, such as the lack of citations to relevant documents or challenges with the disambiguation of author–inventor linkages. To mitigate these limitations, this paper uses Latent Dirichlet Allocation to create topic-based linkages between publications and patents based on the semantic content in the documents. The approach allows for the detection of topical overlap between patent and scientific publications, highlighting topical areas shared by research and application. Using a case study on “Taxol,” a cancer drug, with in total 26 475 documents retrieved from EuropePMC database the study illustrates the performance of the approach. The study offers qualitative and quantitative support that the approach is valuable in detecting patent and publication linkages.
UR - http://www.scopus.com/inward/record.url?scp=85111666612&partnerID=8YFLogxK
U2 - 10.1109/TEM.2019.2923634
DO - 10.1109/TEM.2019.2923634
M3 - Article
SN - 0018-9391
VL - 68
SP - 1786
EP - 1801
JO - IEEE Transactions on Engineering Management
JF - IEEE Transactions on Engineering Management
IS - 6
M1 - 8781878
ER -
