Incremental Integration of Probabilistic Models Learned from Data

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http://doi.ieeecomputersociety.org/10.1109/ICDMW.2007.16

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	Jian Xu, Pedrito Maynard-Zhang, Jianhua Chen, "Incremental Integration of Probabilistic Models Learned from Data," Data Mining Workshops, International Conference on, pp. 519-526, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007.

	BibTex	x
	@article{ 10.1109/ICDMW.2007.16, author = {Jian Xu and Pedrito Maynard-Zhang and Jianhua Chen}, title = {Incremental Integration of Probabilistic Models Learned from Data}, journal ={Data Mining Workshops, International Conference on}, volume = {0}, year = {2007}, isbn = {0-7695-3033-8}, pages = {519-526}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2007.16}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining Workshops, International Conference on TI - Incremental Integration of Probabilistic Models Learned from Data SN - 0-7695-3033-8 SP519 EP526 A1 - Jian Xu, A1 - Pedrito Maynard-Zhang, A1 - Jianhua Chen, PY - 2007 VL - 0 JA - Data Mining Workshops, International Conference on ER -

Jian Xu

Pedrito Maynard-Zhang

Jianhua Chen

This paper addresses multi-source information integra- tion in stochastic environments where information from sources consists of probabilistic domain models (repre- sented as joint distributions or Bayesian networks) learned from data. We extend the batch algorithm proposed by Maynard-Reid II and Chajewska [9] to accommodate incre- mental integration so as to support `anytime' querying. Ex- perimental results verify that our algorithms compare well with the batch algorithm in accuracy and efficiency. Ex- tensions for integrating joint distributions are independent of the order in which sources arrive, but the Bayesian net- work integration extension is only approximately so. This is due to bias introduced by the algorithm's use of heuris- tic optimization, and an `inertial' effect that makes this bias difficult to undo over time.

Citation:

Jian Xu, Pedrito Maynard-Zhang, Jianhua Chen, "Incremental Integration of Probabilistic Models Learned from Data," icdmw, pp.519-526, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007

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