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ICML
2010
IEEE
13 years 9 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
SIGMOD
1999
ACM
108views Database» more  SIGMOD 1999»
14 years 4 days ago
DynaMat: A Dynamic View Management System for Data Warehouses
Pre-computation and materialization of views with aggregate functions is a common technique in Data Warehouses. Due to the complex structure of the warehouse and the different pro...
Yannis Kotidis, Nick Roussopoulos
SDM
2010
SIAM
183views Data Mining» more  SDM 2010»
13 years 9 months ago
GraSS: Graph Structure Summarization
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...
Kristen LeFevre, Evimaria Terzi
WSDM
2009
ACM
176views Data Mining» more  WSDM 2009»
14 years 2 months ago
The web changes everything: understanding the dynamics of web content
The Web is a dynamic, ever changing collection of information. This paper explores changes in Web content by analyzing a crawl of 55,000 Web pages, selected to represent different...
Eytan Adar, Jaime Teevan, Susan T. Dumais, Jonatha...
ATAL
2007
Springer
14 years 2 months ago
Sharing experiences to learn user characteristics in dynamic environments with sparse data
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
David Sarne, Barbara J. Grosz