Glossary
- First-Order Predicate Logic :
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Formal system of mathematical logic that supports reasoning about structures consisting of a domain on which certain relations and functions are defined
- Bayesian Network :
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A graphical representation for the joint probability distribution of a set of random variables. A Bayesian network is specified by a directed acyclic graph whose nodes are the random variables and the conditional probability distributions of the random variables given their parents in the graph
- Markov Network :
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A graphical representation for the joint probability distribution of a set of random variables. A Markov network is specified by an undirected graph whose nodes are the random variables and potential functions defined on the cliques of the graph
- Horn Clause :
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A special class of “if… then” ex-pressions in first-order predicate logic, where the ifcondition is a...
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Recommended Reading
De Raedt L (2008) Logical and relational learning. Springer, Berlin
De Raedt L, Frasconi P, Kersting K, Muggleton S (eds) (2008) Probabilistic inductive logic programming. Lecture notes in artificial intelligence, vol 4911. Springer, Berlin
Getoor L, Taskar B (eds) (2007) Introduction to statistical relational learning. MIT, Cambridge
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Jaeger, M. (2014). Probabilistic Logic and Relational Models. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6170-8_157
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