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1
Finding Chunks In Symbolic Time Series
In: http://www.amristar.com.au/~hutch/phd/research1.ps.gz (1999)
Abstract: | The instantaneous entropy of a predictive model is generally recognised as a good indicator of where the boundary between two words lies in natural language text. In the current paper, we present various methods for nding chunks in symbolic time series using measures from information theory, and we show how these chunks may be used to UpWrite the series to a more abstract representation, which brings distant symbols closer together to alleviate the long-distance dependency problem faced by certain classes of predictive models, such as Hidden Markov Models. We show how these chunking methods may be used to segment natural language text, and we speculate on applications in adaptive data compression. Keywords|Data compression, entropic chunking, text segmentation, grammatical inference. I. Introduction W E consider the problem of nding chunks|more or less well-dened strings of symbols|in symbolic time series; that is, nding sequences of symbols which constitute intermediate symb.
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.6035
http://www.amristar.com.au/~hutch/phd/research1.ps.gz
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2
The NonI Conversation Simulator
In: http://ciips.ee.uwa.edu.au/~hutch/phd/research9.ps.gz (1998)
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3
Finding Structure via Compression
In: http://ciips.ee.uwa.edu.au/~hutch/phd/conference2.ps.gz (1998)
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4
Language Acquisition and Data Compression
In: http://ciips.ee.uwa.edu.au/~hutch/phd/conference1.ps.gz (1997)
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5
Finding Structure in the Vowel Space
In: http://ciips.ee.uwa.edu.au/Papers/Conference_Papers/1993/04/cp93-04.ps.gz (1993)
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6
Affine Transformations of the Speech Space
In: http://ciips.ee.uwa.edu.au/Papers/Conference_Papers//1992/03//cp92-03.ps.gz (1992)
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7
Introducing MegaHAL
In: http://ciips.ee.uwa.edu.au/~hutch/phd/conference3.ps.gz
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