Schemas and Models
D. Jensen and J. Neville (2002). Schemas and models. Proceedings of the Multi-Relational Data Mining Workshop, 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
- Abstract
- We propose the Schema-Model Framework, which characterizes algorithms that learn probabilistic models from relational data as having two parts: a schema that identifies sets of related data items and groups them into relevant categories; and a model that allows probabilistic inference about those data itesm. The framework highlights how relational learning techniques must structure their own learning tasks in ways that propositional learners do not. The framework also highlights interesting directions for future research in relational learning.
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