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» Learning from Highly Structured Data by Decomposition
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PERCOM
2007
ACM
15 years 9 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
WEBDB
2010
Springer
168views Database» more  WEBDB 2010»
15 years 2 months ago
WikiAnalytics: Disambiguation of Keyword Search Results on Highly Heterogeneous Structured Data
Wikipedia infoboxes is an example of a seemingly structured, yet extraordinarily heterogeneous dataset, where any given record has only a tiny fraction of all possible fields. Su...
Andrey Balmin, Emiran Curtmola
UAI
1998
14 years 11 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper
IDEAL
2007
Springer
15 years 3 months ago
A New Dissimilarity Measure Between Trees by Decomposition of Unit-Cost Edit Distance
Abstract. Tree edit distance is a conventional dissimilarity measure between labeled trees. However, tree edit distance including unit-cost edit distance contains the similarity of...
Hisashi Koga, Hiroaki Saito, Toshinori Watanabe, T...
98
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CIKM
2008
Springer
14 years 11 months ago
Structure feature selection for graph classification
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining...
Hongliang Fei, Jun Huan