An unsupervised algorithm for segmenting categorical timeseries into episodes

Paul Cohen, Brent Heeringa, Niall M. Adams

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

This paper describes an unsupervised algorithm for segmentingcateg orical time series into episodes. The Voting-Experts algorithm first collects statistics about the frequency and boundary entropy of ngrams, then passes a window over the series and has two "expert methods" decide where in the window boundaries should be drawn. The algorithm successfully segments text into words in four languages. The algorithm also segments time series of robot sensor data into subsequences that represent episodes in the life of the robot. We claim that Voting- Experts finds meaningful episodes in categorical time series because it exploits two statistical characteristics of meaningful episodes.

Original languageEnglish (US)
Title of host publicationPattern Detection and Discovery - ESF Exploratory Workshop, Proceedings
EditorsDavid J. Hand, Niall M. Adams, Richard J. Bolton
PublisherSpringer-Verlag
Pages49-62
Number of pages14
ISBN (Electronic)9783540441489
DOIs
StatePublished - 2002
EventESF Exploratory Workshop on Pattern Detection and Discovery, 2002 - London, United Kingdom
Duration: Sep 16 2002Sep 19 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2447
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherESF Exploratory Workshop on Pattern Detection and Discovery, 2002
CountryUnited Kingdom
CityLondon
Period9/16/029/19/02

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'An unsupervised algorithm for segmenting categorical timeseries into episodes'. Together they form a unique fingerprint.

  • Cite this

    Cohen, P., Heeringa, B., & Adams, N. M. (2002). An unsupervised algorithm for segmenting categorical timeseries into episodes. In D. J. Hand, N. M. Adams, & R. J. Bolton (Eds.), Pattern Detection and Discovery - ESF Exploratory Workshop, Proceedings (pp. 49-62). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2447). Springer-Verlag. https://doi.org/10.1007/3-540-45728-3_5