Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks
Statistical Relational Learning (SRL) approaches have been developed to learn in presence of noisy relational data by combining probability theory with first order logic. While powerful, most learning approaches for these models do not scale well to large datasets. While advances have been made on u...
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Published in | Inductive Logic Programming Vol. 10326; pp. 14 - 26 |
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Main Authors | , , , , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2017
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Online Access | Get full text |
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