Voting experts: An unsupervised algorithm for segmenting sequences

Paul Cohen; Niall Adams; Brent Heeringa

doi:10.3233/ida-2007-11603

Voting experts: An unsupervised algorithm for segmenting sequences

Paul Cohen, Niall Adams, Brent Heeringa

Research output: Contribution to journal › Article › peer-review

45 Scopus citations

Abstract

We describe a statistical signature of chunks and an algorithm for finding chunks. While there is no formal definition of chunks, they may be reliably identified as configurations with low internal entropy or unpredictability and high entropy at their boundaries. We show that the log frequency of a chunk is a measure of its internal entropy. The Voting-Experts exploits the signature of chunks to find word boundaries in text from four languages and episode boundaries in the activities of a mobile robot.

Original language	English (US)
Pages (from-to)	607-625
Number of pages	19
Journal	Intelligent Data Analysis
Volume	11
Issue number	6
DOIs	https://doi.org/10.3233/ida-2007-11603
State	Published - 2007

ASJC Scopus subject areas

Theoretical Computer Science
Computer Vision and Pattern Recognition
Artificial Intelligence

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10.3233/ida-2007-11603

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abstract = "We describe a statistical signature of chunks and an algorithm for finding chunks. While there is no formal definition of chunks, they may be reliably identified as configurations with low internal entropy or unpredictability and high entropy at their boundaries. We show that the log frequency of a chunk is a measure of its internal entropy. The Voting-Experts exploits the signature of chunks to find word boundaries in text from four languages and episode boundaries in the activities of a mobile robot.",

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Voting experts: An unsupervised algorithm for segmenting sequences

Abstract

ASJC Scopus subject areas

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