Electronic Journal of Statistics

Modeling temporal text streams using the local multinomial model

Guy Lebanon, Yang Zhao, and Yanjun Zhao

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Abstract

Temporal text data such as news feeds cannot be adequately modeled by standard n-grams which correspond to multinomial or Markov chain models. Instead, we examine the application of local n-grams to modeling time stamped documents. We derive the asymptotic bias and variance and consider the bandwidth selection problem. Experimental results are presented on news feeds and web search query logs.

Article information

Source
Electron. J. Statist., Volume 4 (2010), 566-584.

Dates
First available in Project Euclid: 16 June 2010

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1276694115

Digital Object Identifier
doi:10.1214/09-EJS522

Mathematical Reviews number (MathSciNet)
MR2660533

Zentralblatt MATH identifier
1329.62244

Subjects
Primary: 62G99: None of the above, but in this section
Secondary: 62P99: None of the above, but in this section

Keywords
Kernel smoothing text modeling

Citation

Lebanon, Guy; Zhao, Yang; Zhao, Yanjun. Modeling temporal text streams using the local multinomial model. Electron. J. Statist. 4 (2010), 566--584. doi:10.1214/09-EJS522. https://projecteuclid.org/euclid.ejs/1276694115


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References

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The Institute of Mathematical Statistics and the Bernoulli Society

Electronic Journal of Statistics

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