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» Models for Representing Task Ontologies
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ICML
2000
IEEE
15 years 10 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
DMSN
2009
ACM
15 years 4 months ago
Message models and aggregation in knowledge based middleware for rich sensor systems
Networked, distributed real world sensing is an increasingly prominent topic in computing and has quickly expanded from resource constrained “sensor networks” measuring simple...
Joseph B. Kopena, William C. Regli, Boon Thau Loo
PKDD
2005
Springer
122views Data Mining» more  PKDD 2005»
15 years 3 months ago
A Probabilistic Clustering-Projection Model for Discrete Data
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
HUMO
2000
Springer
15 years 1 months ago
Modeling the Constraints of Human Hand Motion
Hand motion capturing is one of the most important parts of gesture interfaces. Many current approaches to this task generally involve a formidable nonlinear optimization problem ...
John Y. Lin, Ying Wu, Thomas S. Huang
BMVC
2002
15 years 10 days ago
Modelling life cycle related and individual shape variation in biological specimens
The main purpose of this research is to develop methods for automatic identification of biological specimens in digital photographs and drawings held in a database. Incorporation ...
Y. A. Hicks, A. David Marshall, Ralph R. Martin, P...