A Bayesian Mixture Model for Term Re-occurrence and Burstiness

  title={A Bayesian Mixture Model for Term Re-occurrence and Burstiness},
  author={Avik Sarkar and Paul H. Garthwaite and Anne N. De Roeck},
This paper proposes a model for term reoccurrence in a text collection based on the gaps between successive occurrences of a term. These gaps are modeled using a mixture of exponential distributions. Parameter estimation is based on a Bayesian framework that allows us to fit a flexible model. The model provides measures of a term’s re-occurrence rate and withindocument burstiness. The model works for all kinds of terms, be it rare content word, medium frequency term or frequent function word. A… CONTINUE READING
Highly Cited
This paper has 22 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 14 extracted citations

Similar Papers

Loading similar papers…