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SDM
2010
SIAM
256views Data Mining» more  SDM 2010»
10 years 5 months ago
The Application of Statistical Relational Learning to a Database of Criminal and Terrorist Activity
We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news ar...
B. Delaney, Andrew S. Fast, W. M. Campbell, C. J. ...
WEBI
2005
Springer
10 years 9 months ago
A Novel Way of Computing Similarities between Nodes of a Graph, with Application to Collaborative Recommendation
This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted, undirected, graph. It is based on a M...
François Fouss, Alain Pirotte, Marco Saeren...
ILP
2007
Springer
10 years 10 months ago
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
Statistical Relational Learning (SRL) combines the benefits of probabilistic machine learning approaches with complex, structured domains from Inductive Logic Programming (ILP). W...
Mark Goadrich, Jude W. Shavlik
ALT
2004
Springer
11 years 1 months ago
Probabilistic Inductive Logic Programming
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
Luc De Raedt, Kristian Kersting
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
11 years 4 months ago
Relational data pre-processing techniques for improved securities fraud detection
Commercial datasets are often large, relational, and dynamic. They contain many records of people, places, things, events and their interactions over time. Such datasets are rarel...
Andrew Fast, Lisa Friedland, Marc Maier, Brian Tay...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
11 years 4 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
ICML
2007
IEEE
11 years 5 months ago
Statistical predicate invention
We propose statistical predicate invention as a key problem for statistical relational learning. SPI is the problem of discovering new concepts, properties and relations in struct...
Stanley Kok, Pedro Domingos
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