WMPLP: A model for link prediction in heterogeneous social networks

Heterogeneous social networks present a great challenge for link mining tasks and especially for link prediction. Recent work insists on the importance of information heterogeneity intelligent exploitation in order to achieve best results. That will be more possible only with the development of new...

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Bibliographic Details
Published in2014 4th International Symposium ISKO-Maghreb: Concepts and Tools for knowledge Management (ISKO-Maghreb) pp. 1 - 4
Main Authors Mohdeb, Djamila, Boubetra, Abdelhak, Charikhi, Mourad
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2014
Subjects
Computational modeling
Data mining
Educational institutions
Feature extraction
Heterogeneous social networks
Link prediction
Link strength
Predictive models
Random walks
Social network services
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Summary:Heterogeneous social networks present a great challenge for link mining tasks and especially for link prediction. Recent work insists on the importance of information heterogeneity intelligent exploitation in order to achieve best results. That will be more possible only with the development of new techniques that may represent heterogeneous network in an effective way making it possible to simplify the task of prediction. In this paper, we propose a new method for link prediction WMPLP (Weighted Meta Path-based Link Prediction) which follows a hybrid approach between meta-path prediction methodology and supervised random walks relational methodology.
DOI:10.1109/ISKO-Maghreb.2014.7033447