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» Phenomenal Data Mining: From Data to Phenomena
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KDD
2008
ACM
120views Data Mining» more  KDD 2008»
16 years 7 months ago
Entity categorization over large document collections
Extracting entities (such as people, movies) from documents and identifying the categories (such as painter, writer) they belong to enable structured querying and data analysis ov...
Arnd Christian König, Rares Vernica, Venkates...
KDD
2006
ACM
157views Data Mining» more  KDD 2006»
16 years 7 months ago
Using structure indices for efficient approximation of network properties
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...
Matthew J. Rattigan, Marc Maier, David Jensen
EDBT
2010
ACM
184views Database» more  EDBT 2010»
16 years 1 months ago
Aggregation of asynchronous electric power consumption time series knowing the integral
More and more data mining algorithms are applied to a large number of long time series issued by many distributed sensors. The consequence of the huge volume of data is that data ...
Raja Chiky, Laurent Decreusefond, Georges Hé...
ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
16 years 1 months ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
ICDM
2006
IEEE
89views Data Mining» more  ICDM 2006»
16 years 25 days ago
On the Lower Bound of Local Optimums in K-Means Algorithm
The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, ...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung