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A New Distance Measure for Model-Based Sequence Clustering
July 2009 (vol. 31 no. 7)
pp. 1325-1331
ASCII Text
x 
 
Darío García-García, Emilio Parrado Hernández, Fernando Díaz-de María, "A New Distance Measure for Model-Based Sequence Clustering," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 7, pp. 1325-1331, July, 2009.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2008.268,
author = {Darío García-García and Emilio Parrado Hernández and Fernando Díaz-de María},
title = {A New Distance Measure for Model-Based Sequence Clustering},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {31},
number = {7},
issn = {0162-8828},
year = {2009},
pages = {1325-1331},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.268},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - A New Distance Measure for Model-Based Sequence Clustering
IS - 7
SN - 0162-8828
SP1325
EP1331
EPD - 1325-1331
A1 - Darío García-García,
A1 - Emilio Parrado Hernández,
A1 - Fernando Díaz-de María,
PY - 2009
KW - Clustering
KW - sequential data
KW - similarity measures.
VL - 31
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Darío García-García, University Carlos III of Madrid, Madrid
Emilio Parrado Hernández, University Carlos III of Madrid, Madrid
Fernando Díaz-de María, University Carlos III of Madrid, Madrid
We review the existing alternatives for defining model-based distances for clustering sequences and propose a new one based on the Kullback-Leibler divergence. This distance is shown to be especially useful in combination with spectral clustering. For improved performance in real-world scenarios, a model selection scheme is also proposed.

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Index Terms:
Clustering, sequential data, similarity measures.
Citation:
Darío García-García, Emilio Parrado Hernández, Fernando Díaz-de María, "A New Distance Measure for Model-Based Sequence Clustering," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 7, pp. 1325-1331, July 2009, doi:10.1109/TPAMI.2008.268
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