Probabilistic Relational Model (PRM)

A Probabilistic Relational Model (PRM) is a Statistical Model that is a Relational Model.

• AKA: PRM.
• See: Probabilistic Relational Learning.

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References

2002

• (Getoor et al., 2002) ⇒ Lise Getoor, Nir Fridman, Daphne Koller, and Benjamin Taskar. (2002). “Learning Probabilistic Models of Link Structure.” In: Journal Machine Learning Research, 3.

2000

• (Getoor, 2000) ⇒ Lise Getoor. (2000). “Learning Probabilistic Relational Models.” In: 4th International Symposium on Abstraction, Reformulation, and Approximation (SARA 2000). doi:10.1007/3-540-44914-0.
  • QUOTE: A PRM describes a template for a probability distribution over a database. The template includes a relational component, that describes the relational schema for the domain, and a probabilistic component, that describes the probabilistic dependencies that hold in the domain. A PRM, together with a particular database of objects, defines a probability distribution over the attributes of the objects and the relations that hold between them. The relational component describes entities in the model, attributes of each entity, and references from one entity to another. The probabilistic component describes dependencies among attributes, both within the same entity and between attributes in related entities.

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