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» Mining Multiple Large Databases
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VLDB
2008
ACM
147views Database» more  VLDB 2008»
14 years 10 months ago
Tree-based partition querying: a methodology for computing medoids in large spatial datasets
Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous e...
Kyriakos Mouratidis, Dimitris Papadias, Spiros Pap...
NAACL
2004
13 years 11 months ago
Answering Definition Questions Using Multiple Knowledge Sources
Definition questions represent a largely unexplored area of question answering--they are different from factoid questions in that the goal is to return as many relevant "nugg...
Wesley Hildebrandt, Boris Katz, Jimmy J. Lin
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
14 years 4 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...
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
14 years 4 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
KDD
1995
ACM
173views Data Mining» more  KDD 1995»
14 years 1 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