AutoMode: Relational Learning With Less Black Magic

摘要

Relational learning algorithms learn the Datalog definition of novel relations in terms of existing relations in the database. In order to effectively use these algorithms, users must constraint the space of candidate definitions by specifying a language bias. Unfortunately, specifying the language bias takes a great deal of time and effort, as it is done via trial and error and is guided by the expert's intuitions. We demonstrate AutoMode, a system that leverages information in the schema and content of the database to automatically induce the language bias used by popular relational learning algorithms.