An evolutionary approach to constructive induction for link discovery

Authors:
Tim Weninger;William H. Hsu;Jing Xia;Waleed Aljandal
Affiliations:
Kansas State University, Manhattan, KS, USA;Kansas State University, Manhattan, KS, USA;Kansas State University, Manhattan, KS, USA;Kansas State University, Manhattan, KS, USA
Venue:
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Year:
2009

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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.