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» Mining Very Large Databases
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133
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COSIT
2003
Springer
145views GIS» more  COSIT 2003»
15 years 7 months ago
Extracting Landmarks with Data Mining Methods
Abstract. The navigation task is a very demanding application for mobile users. The algorithms of present software solutions are based on the established methods of car navigation ...
Birgit Elias
120
Voted
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
15 years 8 months ago
Spatial Multidimensional Sequence Clustering
Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measureme...
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se...
111
Voted
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
15 years 9 months ago
Representing Tuple and Attribute Uncertainty in Probabilistic Databases
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources — sensor data, experimental data, data from ...
Prithviraj Sen, Amol Deshpande, Lise Getoor
116
Voted
KDD
1995
ACM
173views Data Mining» more  KDD 1995»
15 years 6 months ago
Knowledge Discovery in Textual Databases (KDT)
The information age is characterizedby a rapid growth in the amountof information availablein electronicmedia. Traditional data handling methods are not adequate to cope with this...
Ronen Feldman, Ido Dagan
215
Voted
SIGMOD
2008
ACM
191views Database» more  SIGMOD 2008»
16 years 2 months ago
Efficient aggregation for graph summarization
Graphs are widely used to model real world objects and their relationships, and large graph datasets are common in many application domains. To understand the underlying character...
Yuanyuan Tian, Richard A. Hankins, Jignesh M. Pate...