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Clustering scientific documents with topic modeling
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Cited by:
- Tosi, Mauro Dalle Lucca & dos Reis, Julio Cesar, 2021. "SciKGraph: A knowledge graph approach to structure a scientific field," Journal of Informetrics, Elsevier, vol. 15(1).
- Tingcan Ma & Ruinan Li & Guiyan Ou & Mingliang Yue, 2018. "Topic based research competitiveness evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 789-803, November.
- Alexey Lyutov & Yilmaz Uygun & Marc-Thorsten Hütt, 2021. "Machine learning misclassification of academic publications reveals non-trivial interdependencies of scientific disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1173-1186, February.
- Kyuwoong Kim & Kyeongmin Park & Sungjoo Lee, 2019. "Investigating technology opportunities: the use of SAOx analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 45-70, January.
- Aminath Shausan & Aapeli Vuorinen, 2023. "Thirty-six years of contributions to queueing systems: a content analysis, topic modeling, and graph-based exploration of research published in the QUESTA journal," Queueing Systems: Theory and Applications, Springer, vol. 104(1), pages 3-18, June.
- Afful-Dadzie, Eric & Afful-Dadzie, Anthony, 2017. "Liberation of public data: Exploring central themes in open government data and freedom of information research," International Journal of Information Management, Elsevier, vol. 37(6), pages 664-672.
- Doo-San Kim & Byeong-Cheol Lee & Kwang-Hi Park, 2021. "Determination of Motivating Factors of Urban Forest Visitors through Latent Dirichlet Allocation Topic Modeling," IJERPH, MDPI, vol. 18(18), pages 1-14, September.
- Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
- Takano, Yasutomo & Mejia, Cristian & Kajikawa, Yuya, 2016. "Unconnected component inclusion technique for patent network analysis: Case study of Internet of Things-related technologies," Journal of Informetrics, Elsevier, vol. 10(4), pages 967-980.
- Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
- Arash Hajikhani & Arho Suominen, 2022. "Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6661-6693, November.
- Xie, Zheng & Lv, Yiqin & Song, Yiping & Wang, Qi, 2024. "Data labeling through the centralities of co-reference networks improves the classification accuracy of scientific papers," Journal of Informetrics, Elsevier, vol. 18(2).
- Christian Weismayer & Ilona Pezenka, 2017. "Identifying emerging research fields: a longitudinal latent semantic keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1757-1785, December.
- Sun, Bixuan & Kolesnikov, Sergey & Goldstein, Anna & Chan, Gabriel, 2021. "A dynamic approach for identifying technological breakthroughs with an application in solar photovoltaics," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
- Max Weber & Taha Chaiechi & Rabiul Beg, 2022. "Inclusive Growth and Climate Change Mitigation Programs and Policies in the ASEAN: Fiscal Implications," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 189-220.
- Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
- Sabrina L. Woltmann & Lars Alkærsig, 2018. "Tracing university–industry knowledge transfer through a text mining approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 449-472, October.
- Alice Tontodimamma & Eugenia Nissi & Annalina Sarra & Lara Fontanella, 2021. "Thirty years of research into hate speech: topics of interest and their evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 157-179, January.
- Frank Havemann & Jochen Gläser & Michael Heinz, 2017. "Memetic search for overlapping topics based on a local evaluation of link communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1089-1118, May.
- Yuan Zhou & Heng Lin & Yufei Liu & Wei Ding, 2019. "A novel method to identify emerging technologies using a semi-supervised topic clustering model: a case of 3D printing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 167-185, July.
- Arho Suominen & Ozgur Dedehayir, 2017. "Pathways To A Drug: A Mixed Methods Analysis Of Emergence," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-17, December.
- Karoliina Isoaho & Fanni Moilanen & Arho Toikka, 2019. "A Big Data View of the European Energy Union: Shifting from ‘a Floating Signifier’ to an Active Driver of Decarbonisation?," Politics and Governance, Cogitatio Press, vol. 7(1), pages 28-44.
- Xiaoyao Han, 2020. "Evolution of research topics in LIS between 1996 and 2019: an analysis based on latent Dirichlet allocation topic model," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2561-2595, December.
- Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
- Zhang, Yi & Zhang, Guangquan & Chen, Hongshu & Porter, Alan L. & Zhu, Donghua & Lu, Jie, 2016. "Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 179-191.
- Max Weber & Taha Chaiechi & Rabiul Beg, 2022. "Inclusive Growth and Climate Change Mitigation Programs and Policies in the ASEAN: Fiscal Implications," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 189-221.
- Amiri, Babak & Karimianghadim, Ramin, 2024. "A novel text clustering model based on topic modelling and social network analysis," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
- Huailan Liu & Zhiwang Chen & Jie Tang & Yuan Zhou & Sheng Liu, 2020. "Mapping the technology evolution path: a novel model for dynamic topic detection and tracking," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2043-2090, December.
- Wei Du & Raymond Yiu Keung Lau & Jian Ma & Wei Xu, 2015. "A multi-faceted method for science classification schemes (SCSs) mapping in networking scientific resources," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2035-2056, December.
- Samira Ranaei & Arho Suominen & Alan Porter & Stephen Carley, 2020. "Evaluating technological emergence using text analytics: two case technologies and three approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 215-247, January.
- Jiang, Hanchen & Qiang, Maoshan & Lin, Peng, 2016. "A topic modeling based bibliometric exploration of hydropower research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 226-237.
- Ma, Tingting & Zhou, Xiao & Liu, Jia & Lou, Zhenkai & Hua, Zhaoting & Wang, Ruitao, 2021. "Combining topic modeling and SAO semantic analysis to identify technological opportunities of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
- McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
- Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
- Yeow Chong Goh & Xin Qing Cai & Walter Theseira & Giovanni Ko & Khiam Aik Khor, 2020. "Evaluating human versus machine learning performance in classifying research abstracts," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1197-1212, November.
- Hoang, Yen Hai & Ngo, Vu Minh & Bich Vu, Ngoc, 2023. "Central bank digital currency: A systematic literature review using text mining approach," Research in International Business and Finance, Elsevier, vol. 64(C).
- Shuo Xu & Junwan Liu & Dongsheng Zhai & Xin An & Zheng Wang & Hongshen Pang, 2018. "Overlapping thematic structures extraction with mixed-membership stochastic blockmodel," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 61-84, October.
- Ting Xiong & Liang Zhou & Ying Zhao & Xiaojuan Zhang, 2022. "Mining semantic information of co-word network to improve link prediction performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 2981-3004, June.
- Takano, Yasutomo & Kajikawa, Yuya, 2019. "Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 45-68.
- Andrea Zielinski, 2022. "Impact of model settings on the text-based Rao diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7751-7768, December.