References in zbMATH (referenced in 15 articles , 1 standard article )

Showing results 1 to 15 of 15.
Sorted by year (citations)

  1. Jonas Rieger: ldaPrototype: A method in R to get a Prototype of multiple Latent Dirichlet Allocations (2020) not zbMATH
  2. Liao, Xiyue; Chen, Guoqiang; Ku, Ben; Narula, Rahul; Duncan, Janet: Text mining methods applied to insurance company customer calls: a case study (2020)
  3. Margaret Roberts; Brandon Stewart; Dustin Tingley: stm: An R Package for Structural Topic Models (2019) not zbMATH
  4. Rieger, Jonas: Book review of: Mónica Bécue-Bertaut, Textual data science with R (2019)
  5. Sekiguchi, Takuya: Preferences over procedures and outcomes in judgment aggregation: an experimental study (2019)
  6. Aggarwal, Charu C.: Machine learning for text (2018)
  7. Bouveyron, C.; Latouche, P.; Zreik, R.: The stochastic topic block model for the clustering of vertices in networks with textual edges (2018)
  8. Gudivada, Venkat N.; Arbabifard, Kamyar: Open-source libraries, application frameworks, and workflow systems for NLP (2018)
  9. Mair, Patrick: Modern psychometrics with R (2018)
  10. Mankad, Shawn; Hu, Shengli; Gopal, Anandasivam: Single stage prediction with embedded topic modeling of online reviews for mobile app management (2018)
  11. Zhao, Shiwen; Engelhardt, Barbara E.; Mukherjee, Sayan; Dunson, David B.: Fast moment estimation for generalized latent Dirichlet models (2018)
  12. Taylor B. Arnold: A Tidy Data Model for Natural Language Processing using cleanNLP (2017) arXiv
  13. Rusch, Thomas; Hofmarcher, Paul; Hatzinger, Reinhold; Hornik, Kurt: Model trees with topic model preprocessing: an approach for data journalism illustrated with the WikiLeaks Afghanistan war logs (2013)
  14. Zhao, Yanchang: R and data mining. Examples and case studies (2013)
  15. Bettina Grün; Kurt Hornik: topicmodels: An R Package for Fitting Topic Models (2011) not zbMATH