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ICML
2007
IEEE

Statistical predicate invention

10 years 2 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 structured data, and generalizes hidden variable discovery in statistical models and predicate invention in ILP. We propose an initial model for SPI based on second-order Markov logic, in which predicates as well as arguments can be variables, and the domain of discourse is not fully known in advance. Our approach iteratively refines clusters of symbols based on the clusters of symbols they appear in atoms with (e.g., it clusters relations by the clusters of the objects they relate). Since different clusterings are better for predicting different subsets of the atoms, we allow multiple cross-cutting clusterings. We show that this approach outperforms Markov logic structure learning and the recently introduced infinite relational model on a number of relational datasets.
Stanley Kok, Pedro Domingos
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2007
Where ICML
Authors Stanley Kok, Pedro Domingos
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