Higher Criticism as an Unsupervised Authorship Discriminator Notebook for PAN at CLEF 2020

Alon Kipnis

Higher Criticism as an Unsupervised Authorship Discriminator Notebook for PAN at CLEF 2020

Alon Kipnis

Research output: Contribution to journal › Conference article › peer-review

Abstract

We adapt the Higher Criticism (HC) as an unsupervised untrained discriminator of two documents. Our method takes word-by-word p-values based on a binomial allocation model of words between the documents and combines these p-values to a single test statistic using HC. Large values of HC provide evidence that the two documents are different in terms of authorship. Despite its simplicity, the method achieves competitive results in the Cross-domain Authorship Verification challenge.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	2696
State	Published - 1 Jan 2020
Externally published	Yes
Event	11th Conference and Labs of the Evaluation Forum, CLEF 2020 - virtual, Online, Greece Duration: 22 Sep 2020 → 25 Sep 2020

ASJC Scopus subject areas

General Computer Science

Cite this

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title = "Higher Criticism as an Unsupervised Authorship Discriminator Notebook for PAN at CLEF 2020",

abstract = "We adapt the Higher Criticism (HC) as an unsupervised untrained discriminator of two documents. Our method takes word-by-word p-values based on a binomial allocation model of words between the documents and combines these p-values to a single test statistic using HC. Large values of HC provide evidence that the two documents are different in terms of authorship. Despite its simplicity, the method achieves competitive results in the Cross-domain Authorship Verification challenge.",

author = "Alon Kipnis",

note = "Publisher Copyright: Copyright {\textcopyright} 2020 for this paper by its authors.; 11th Conference and Labs of the Evaluation Forum, CLEF 2020 ; Conference date: 22-09-2020 Through 25-09-2020",

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AU - Kipnis, Alon

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N2 - We adapt the Higher Criticism (HC) as an unsupervised untrained discriminator of two documents. Our method takes word-by-word p-values based on a binomial allocation model of words between the documents and combines these p-values to a single test statistic using HC. Large values of HC provide evidence that the two documents are different in terms of authorship. Despite its simplicity, the method achieves competitive results in the Cross-domain Authorship Verification challenge.

AB - We adapt the Higher Criticism (HC) as an unsupervised untrained discriminator of two documents. Our method takes word-by-word p-values based on a binomial allocation model of words between the documents and combines these p-values to a single test statistic using HC. Large values of HC provide evidence that the two documents are different in terms of authorship. Despite its simplicity, the method achieves competitive results in the Cross-domain Authorship Verification challenge.

UR - https://www.scopus.com/pages/publications/85121829205

M3 - Conference article

AN - SCOPUS:85121829205

SN - 1613-0073

VL - 2696

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 11th Conference and Labs of the Evaluation Forum, CLEF 2020

Y2 - 22 September 2020 through 25 September 2020

ER -

Higher Criticism as an Unsupervised Authorship Discriminator Notebook for PAN at CLEF 2020

Abstract

ASJC Scopus subject areas

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