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» Learning Models for Multi-Source Integration
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AAAI
2007
15 years 2 months ago
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
A traditional goal of Artificial Intelligence research has been a system that can read unrestricted natural language texts on a given topic, build a model of that topic and reason...
Ken Barker, Bhalchandra Agashe, Shaw Yi Chaw, Jame...
MDM
2009
Springer
201views Communications» more  MDM 2009»
15 years 6 months ago
OntoMobiLe: A Generic Ontology-Centric Service-Oriented Architecture for Mobile Learning
Creation of pedagogical learning models to handle the specificity of mobile learning and the inherent constraints of mobile devices is a fundamental challenge in mobile learning. ...
Keng Y. Yee, Wee Tiong Ang, Flora S. Tsai, Rajaram...
RECOMB
2005
Springer
16 years 3 days ago
Towards an Integrated Protein-Protein Interaction Network
Abstract. Protein-protein interactions play a major role in most cellular processes. Thus, the challenge of identifying the full repertoire of interacting proteins in the cell is o...
Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir F...
IQ
2007
15 years 1 months ago
An Alert Management Approach To Data Quality: Lessons Learned From The Visa Data Authority Program
: We introduce an end-to-end framework for data quality that integrates business strategy, data quality models, and supporting investigative and governance processes. We also descr...
Joseph Bugajski, Robert L. Grossman
CVPR
2000
IEEE
16 years 1 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu