Voting experts: An unsupervised algorithm for segmenting sequences

Paul R Cohen, Niall Adams, Brent Heeringa

Research output: Contribution to journalArticle

40 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)607-625
Number of pages19
JournalIntelligent Data Analysis
Volume11
Issue number6
StatePublished - 2007
Externally publishedYes

Fingerprint

Voting
Entropy
Signature
Internal
Mobile Robot
Mobile robots
Configuration

ASJC Scopus subject areas

  • Artificial Intelligence
  • Theoretical Computer Science
  • Computer Vision and Pattern Recognition

Cite this

Voting experts : An unsupervised algorithm for segmenting sequences. / Cohen, Paul R; Adams, Niall; Heeringa, Brent.

In: Intelligent Data Analysis, Vol. 11, No. 6, 2007, p. 607-625.

Research output: Contribution to journalArticle

Cohen, Paul R ; Adams, Niall ; Heeringa, Brent. / Voting experts : An unsupervised algorithm for segmenting sequences. In: Intelligent Data Analysis. 2007 ; Vol. 11, No. 6. pp. 607-625.
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