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ESWS
2008
Springer
15 years 9 months ago
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
Christoph Kiefer, Abraham Bernstein, André ...
PAMI
1998
128views more  PAMI 1998»
15 years 7 months ago
A Hierarchical Latent Variable Model for Data Visualization
—Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multivariate data. Most visualization algorithms aim to find a projec...
Christopher M. Bishop, Michael E. Tipping
ICDE
2006
IEEE
130views Database» more  ICDE 2006»
16 years 8 months ago
Warehousing and Analyzing Massive RFID Data Sets
Radio Frequency Identification (RFID) applications are set to play an essential role in object tracking and supply chain management systems. In the near future, it is expected tha...
Hector Gonzalez, Jiawei Han, Xiaolei Li, Diego Kla...
207
Voted
VIS
2007
IEEE
113views Visualization» more  VIS 2007»
16 years 8 months ago
Texture-based Feature Tracking for Effective Time-varying Data Visualization
Analyzing, visualizing, and illustrating changes within time-varying volumetric data is challenging due to the dynamic changes occurring between timesteps. The changes and variatio...
Jesus Caban, Alark Joshi, Penny Rheingans
KDD
2004
ACM
168views Data Mining» more  KDD 2004»
16 years 7 months ago
Mining, indexing, and querying historical spatiotemporal data
In many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. ...
Nikos Mamoulis, Huiping Cao, George Kollios, Mario...