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Optimal Segmentation Using Tree Models
Hong Kong December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.122Sixth IEEE International Conference o ...
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Robert Gwadera, Aristides Gionis, Heikki Mannila, "Optimal Segmentation Using Tree Models," Data Mining, IEEE International Conference on, pp. 244-253, Sixth IEEE International Conference on Data Mining (ICDM'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICDM.2006.122,
author = {Robert Gwadera and Aristides Gionis and Heikki Mannila},
title = {Optimal Segmentation Using Tree Models},
journal ={Data Mining, IEEE International Conference on},
volume = {0},
year = {2006},
issn = {1550-4786},
pages = {244-253},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.122},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Mining, IEEE International Conference on
TI - Optimal Segmentation Using Tree Models
SN - 1550-4786
SP244
EP253
A1 - Robert Gwadera,
A1 - Aristides Gionis,
A1 - Heikki Mannila,
PY - 2006
KW - null
VL - 0
JA - Data Mining, IEEE International Conference on
ER -
 
Robert Gwadera, University of Helsinki, Finland
Aristides Gionis, University of Helsinki, Finland
Heikki Mannila, University of Helsinki, Finland
Sequence data are abundant in application areas such as computational biology, environmental sciences, and telecommunication. Many real-life sequences have a strong segmental structure, with segments of different complexities. In this paper we study the description of sequence segments using variable length Markov chains (VLMCs), also known as tree models. We discover the segment boundaries of a sequence and at the same time we obtain a VLMC for each segment. Such a context tree contains the probability distribution vectors that capture the essential features of the corresponding segment. We use the Bayesian Information Criterion (BIC) and the Krichevsky-Trofimov Probability (KT) to select the number of segments of a sequence. On DNA data the method selects segments that closely correspond to the annotated regions of the genes.
Citation:
Robert Gwadera, Aristides Gionis, Heikki Mannila, "Optimal Segmentation Using Tree Models," icdm, pp.244-253, Sixth IEEE International Conference on Data Mining (ICDM'06), 2006
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