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Author Blockeel, Hendrik ♦ Bruynooghe, Maurice
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Aggregation Versus Selection Bias ♦ Relational Neural Network ♦ Specific Element ♦ Many Approach ♦ Undesirable Bias ♦ Relational Learner ♦ Attribute Mother ♦ Single Relation Person ♦ Current Relational Learner ♦ Many-to-many Relation
Description Current relational learners handle sets either by aggregating over them or by selecting specific elements, but do not combine both. This imposes a significant, possibly undesirable bias on these learners. We discuss this bias, as well as some ideas on how to lift it. In the process, we introduce the notion of relational neural networks. 1 Biases of Relational Learners Among the many approaches to relational model learning that currently exist, a distinction can be made with respect to how they handle one-to-many and many-to-many relations, or, equivalently, how they handle sets of objects. To illustrate this, consider a database with just a single relation “Person ” with attributes Mother, Father, and Sex.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2003-01-01
Publisher Institution In: IJCAI-2003 Workshop on Learning Statistical Models from Relational Data, SRL-2003