On the approximation of curves by line segments using dynamic programming
Communications of the ACM
DNA segmentation as a model selection process
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Time Series Segmentation for Context Recognition in Mobile Devices
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Optimal DNA Segmentation Based on the MDL Principle
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Using Markov chain Monte Carlo and dynamic programming for event sequence data
Knowledge and Information Systems
The minimum description length principle in coding and modeling
IEEE Transactions on Information Theory
Fast universal coding with context models
IEEE Transactions on Information Theory
Context tree estimation for not necessarily finite memory processes, via BIC and MDL
IEEE Transactions on Information Theory
A universal finite memory source
IEEE Transactions on Information Theory
The context-tree weighting method: basic properties
IEEE Transactions on Information Theory
International Journal of Data Mining and Bioinformatics
Hi-index | 0.00 |
Sequence data are abundant in application areas such as computational biology, environmental sciences, and telecommunications. 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 compute a VLMC for each segment. We use the Bayesian information criterion (BIC) and a variant of the minimum description length (MDL) principle that uses the Krichevsky-Trofimov (KT) code length 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.