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» Learning from Highly Structured Data by Decomposition
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
EMNLP
2010
14 years 8 months ago
Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification
This paper addresses the problem of learning to map sentences to logical form, given training data consisting of natural language sentences paired with logical representations of ...
Tom Kwiatkowksi, Luke S. Zettlemoyer, Sharon Goldw...
ICIP
2005
IEEE
15 years 11 months ago
Presegmentation of high-resolution satellite images with a multifractal reconstruction scheme based on an entropy criterium
The last generation of satellites leads to the very high-resolution images which offer a high quality of detailed information about the Earth's surface. However, the exploita...
Antonio Turiel, Hussein M. Yahia, Jacopo Grazzini
BMCBI
2005
142views more  BMCBI 2005»
14 years 10 months ago
High performance workflow implementation for protein surface characterization using grid technology
Background: This study concerns the development of a high performance workflow that, using grid technology, correlates different kinds of Bioinformatics data, starting from the ba...
Ivan Merelli, Giulia Morra, Daniele D'Agostino, An...
ECTEL
2010
Springer
14 years 7 months ago
GVIS: A Facility for Adaptively Mashing Up and Representing Open Learner Models
In this article we present an infrastructure for creating mash up and visual representations of the user profile that combine data from different sources. We explored this approach...
Luca Mazzola, Riccardo Mazza