Detection of Domain-Specific Trends in Text Collections

  • Ilnur Gadelshin
  • Anna Antonova
  • Dmitry IlvovskyEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 436)


This study considers the problem of automatic trend detection in document collections related to several specific domains. The suggested trend detection algorithm is based on the domain-specific trend model. The algorithm was evaluated on documents from shipbuilding and power engineering domains.


Trend detection Text analysis Document collections 


  1. 1.
    Porter, F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)CrossRefGoogle Scholar
  2. 2.
    Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. Process. Manage. 24(5), 513–523 (1988)CrossRefGoogle Scholar
  3. 3.
    Natural Language Toolkit.
  4. 4.
    Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)zbMATHGoogle Scholar
  5. 5.
    Vorontsov, K.V., Potapenko, A.A.: Regularization, robustness and sparseness of probabilistic topic models. Comput. Res. Model. 2, 161–174 (2012) (in Russian)Google Scholar
  6. 6.
    Teh, Y.W., Jordan, M.I.: Hierarchical Bayesian nonparametric models with applications. In: Hjort, N., Holmes, C., Müller, P., Walker, S. (eds.) Bayesian Nonparametrics Principles and Practice. Cambridge University Press, Cambridge (2009)Google Scholar
  7. 7.
    Teh, Y.W.: Dirichlet processes. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning, pp. 280–287. Springer, Heidelberg (2010)Google Scholar
  8. 8.
    Blei, D, Lafferty, J.: Dynamic topic models. In: ICML (2006)Google Scholar
  9. 9.
    Glance, N., Hurst, M., Tomokiyo, T.: BlogPulse: automated trend discovery for weblogs. In: WWW 2004, ACM (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ilnur Gadelshin
    • 1
  • Anna Antonova
    • 1
  • Dmitry Ilvovsky
    • 1
    Email author
  1. 1.Higher School of EconomicsMoscowRussia

Personalised recommendations