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» Efficient Discovery of Confounders in Large Data Sets
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AMKM
2003
Springer
15 years 11 months ago
Discovering, Visualizing, and Sharing Knowledge through Personalized Learning Knowledge Maps
This paper presents an agent-based approach to semantic exploration and knowledge discovery in large information spaces by means of capturing, visualizing and making usable implic...
Jasminko Novak, Michael Wurst, Monika Fleischmann,...
MLDM
2005
Springer
15 years 12 months ago
CorePhrase: Keyphrase Extraction for Document Clustering
Abstract. The ability to discover the topic of a large set of text documents using relevant keyphrases is usually regarded as a very tedious task if done by hand. Automatic keyphra...
Khaled M. Hammouda, Diego N. Matute, Mohamed S. Ka...
CIKM
2000
Springer
15 years 10 months ago
Scalable association-based text classification
Naïve Bayes (NB) classifier has long been considered a core methodology in text classification mainly due to its simplicity and computational efficiency. There is an increasing n...
Dimitris Meretakis, Dimitris Fragoudis, Hongjun Lu...
IDEAS
1999
IEEE
123views Database» more  IDEAS 1999»
15 years 10 months ago
Improving OLAP Performance by Multidimensional Hierarchical Clustering
Data-warehousing applications cope with enormous data sets in the range of Gigabytes and Terabytes. Queries usually either select a very small set of this data or perform aggregat...
Volker Markl, Frank Ramsak, Rudolf Bayer
ICIP
2004
IEEE
16 years 8 months ago
Rate-distortion analysis of random access for compressed light fields
Image-based rendering data sets, such as light fields, require efficient compression due to their large data size, but also easy random access when rendering from the data set. Ef...
Prashant Ramanathan, Bernd Girod