IDEAS home Printed from https://ideas.repec.org/r/spr/scient/v100y2014i3d10.1007_s11192-014-1321-8.html
   My bibliography  Save this item

Clustering scientific documents with topic modeling

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  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.
  2. 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.
  3. 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.
  4. 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.
  5. 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).
  6. 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.
  7. 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.
  8. 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).
  9. 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.
  10. 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).
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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).
  28. 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.
  29. 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.
  30. 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.
  31. 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).
  32. 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.
  33. 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.
  34. 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.
  35. 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).
  36. 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.
  37. 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.
  38. 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.
  39. 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).
  40. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.