Extensible Markov Model

Brighton, United Kingdom November 01-November 04

DOI Bookmark:

http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10067

Fourth IEEE International Conference ...

	This Article
	PURCHASE ARTICLE: $19 PDF HTML IEEE Xplore Subscribers
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Margaret H. Dunham Articles by Yu Meng Articles by Jie Huang

	ASCII Text	x
	Margaret H. Dunham, Yu Meng, Jie Huang, "Extensible Markov Model," Data Mining, IEEE International Conference on, pp. 371-374, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004.

	BibTex	x
	@article{ 10.1109/ICDM.2004.10067, author = {Margaret H. Dunham and Yu Meng and Jie Huang}, title = {Extensible Markov Model}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2142-8}, pages = {371-374}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10067}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - Extensible Markov Model SN - 0-7695-2142-8 SP371 EP374 A1 - Margaret H. Dunham, A1 - Yu Meng, A1 - Jie Huang, PY - 2004 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

Margaret H. Dunham, Southern Methodist University, Dallas, Texas

Yu Meng, Southern Methodist University, Dallas, Texas

Jie Huang, The University of Texas Southwestern, Dallas, Texas

A Markov Chain is a popular data modeling tool. This paper presents a variation of Markov Chain, namely Extensible Markov Model (EMM). By providing a dynamically adjustable structure, EMM overcomes the problems caused by the static nature of the traditional Markov Chain. Therefore, EMMs are particularly well suited to model spatiotemporal data such as network traffic, environmental data, weather data, and automobile traffic. Performance studies using EMMs for spatiotemporal prediction problems show the advantages of this approach.

Citation:

Margaret H. Dunham, Yu Meng, Jie Huang, "Extensible Markov Model," icdm, pp.371-374, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.