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Learning Over Dirty Data Without Cleaning
We propose DLearn, a novel relational learning system that learns directly over dirty databases effectively and efficiently without any preprocessing.
Usable & Scalable Learning Over Relational Data With Automatic Language Bias
Relational databases are valuable resources for learning novel and interesting relations and concepts.
Schema Independent Relational Learning
In this paper, we introduce and formalize the property of schema independence of relational learning algorithms, and study both the theoretical and empirical dependence of existing algorithms on the common class of (de) composition schema transformations.
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