abstract = "This paper presents a genetic programming-based
symbolic regression approach to the construction of
relational features in link analysis applications.
Specifically, we consider the problems of predicting,
classifying and annotating friends relations in friends
networks, based upon features constructed from network
structure and user profile data. We explain how the
problem of classifying a user pair in a social network,
as directly connected or not, poses the problem of
selecting and constructing relevant features. We use
genetic programming to construct features, represented
by multiple symbol trees with base features as their
leaves. In this manner, the genetic program selects and
constructs features that may not have been originally
considered, but possess better predictive properties
than the base features. Finally, we present
classification results and compare these results with
those of the control and similar approaches.",
notes = "GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).