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» Learning Object Representations Using Sequential Patterns
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PR
2007
81views more  PR 2007»
13 years 7 months ago
Graph embedding using tree edit-union
In this paper we address the problem of how to learn a structural prototype that can be used to represent the variations present in a set of trees. The prototype serves as a patte...
Andrea Torsello, Edwin R. Hancock
ALT
2008
Springer
14 years 4 months ago
Computational Models of Neural Representations in the Human Brain
Abstract For many centuries scientists have wondered how the human brain represents thoughts in terms of the underlying biology of neural activity. Philosophers, linguists, cogniti...
Tom M. Mitchell
TKDE
2008
156views more  TKDE 2008»
13 years 7 months ago
A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns ident...
Yan Huang, Liqin Zhang, Pusheng Zhang
PR
2010
147views more  PR 2010»
13 years 5 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
WWW
2004
ACM
14 years 8 months ago
Ontological representation of learning objects: building interoperable vocabulary and structures
The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Jian Qin, Naybell Hernández