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» On Multiple Query Optimization in Data Mining
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CINQ
2004
Springer
163views Database» more  CINQ 2004»
14 years 1 months ago
Frequent Itemset Discovery with SQL Using Universal Quantification
Algorithms for finding frequent itemsets fall into two broad classes: (1) algorithms that are based on non-trivial SQL statements to query and update a database, and (2) algorithms...
Ralf Rantzau
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 8 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 8 months ago
Extracting shared subspace for multi-label classification
Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construc...
Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 10 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Practical guide to controlled experiments on the web: listen to your customers not to the hippo
The web provides an unprecedented opportunity to evaluate ideas quickly using controlled experiments, also called randomized experiments (single-factor or factorial designs), A/B ...
Ron Kohavi, Randal M. Henne, Dan Sommerfield