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KDD
2003
ACM
149views Data Mining» more  KDD 2003»
14 years 7 months ago
Knowledge-based data mining
We describe techniques for combining two types of knowledge systems: expert and machine learning. Both the expert system and the learning system represent information by logical d...
Søren Damgaard, Sholom M. Weiss, Shubir Kap...
ICML
2005
IEEE
14 years 8 months ago
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Stanley Kok, Pedro Domingos
ECAI
2004
Springer
14 years 22 days ago
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
SEMWEB
2009
Springer
14 years 1 months ago
An Algorithm for Learning with Probabilistic Description Logics
Probabilistic Description Logics are the basis of ontologies in the Semantic Web. Knowledge representation and reasoning for these logics have been extensively explored in the last...
José Eduardo Ochoa Luna, Fabio Gagliardi Co...
DATAMINE
1999
152views more  DATAMINE 1999»
13 years 7 months ago
Discovery of Frequent DATALOG Patterns
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Luc Dehaspe, Hannu Toivonen