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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 8 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
KDD
2005
ACM
182views Data Mining» more  KDD 2005»
14 years 8 months ago
Making holistic schema matching robust: an ensemble approach
The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. As an essential task toward integrating these m...
Bin He, Kevin Chen-Chuan Chang
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 8 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
KDD
2003
ACM
109views Data Mining» more  KDD 2003»
14 years 8 months ago
Experimental design for solicitation campaigns
Data mining techniques are routinely used by fundraisers to select those prospects from a large pool of candidates who are most likely to make a financial contribution. These tech...
Uwe F. Mayer, Armand Sarkissian
EDBT
2006
ACM
105views Database» more  EDBT 2006»
14 years 7 months ago
HASE: A Hybrid Approach to Selectivity Estimation for Conjunctive Predicates
Current methods for selectivity estimation fall into two broad categories, synopsis-based and sampling-based. Synopsis-based methods, such as histograms, incur minimal overhead at ...
Xiaohui Yu, Nick Koudas, Calisto Zuzarte
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