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» Approximate data mining in very large relational data
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VLDB
2004
ACM
120views Database» more  VLDB 2004»
15 years 7 months ago
Relational link-based ranking
Link analysis methods show that the interconnections between web pages have lots of valuable information. The link analysis methods are, however, inherently oriented towards analy...
Floris Geerts, Heikki Mannila, Evimaria Terzi
CLUSTER
2005
IEEE
15 years 7 months ago
A pipelined data-parallel algorithm for ILP
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly...
Nuno A. Fonseca, Fernando M. A. Silva, Víto...
VLDB
2004
ACM
161views Database» more  VLDB 2004»
16 years 2 months ago
Supporting top-k join queries in relational databases
Ranking queries produce results that are ordered on some computed score. Typically, these queries involve joins, where users are usually interested only in the top-k join results....
Ihab F. Ilyas, Walid G. Aref, Ahmed K. Elmagarmid
WAIM
2009
Springer
15 years 6 months ago
Kernel-Based Transductive Learning with Nearest Neighbors
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...
Liangcai Shu, Jinhui Wu, Lei Yu, Weiyi Meng
CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 9 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson