RELISON: A Framework for Link Recommendation in Social Networks

Sanz-Cruzado Puig, J. and Castells, P. (2022) RELISON: A Framework for Link Recommendation in Social Networks. In: SIGIR 2022: 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11-15 Jul 2022, pp. 2992-3002. ISBN 9781450387323 (doi: 10.1145/3477495.3531730)

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Abstract

Link recommendation is an important and compelling problem at the intersection of recommender systems and online social networks. Given a user, link recommenders identify people in the platform the user might be interested in interacting with. We present RELISON, an extensible framework for running link recommendation experiments. The library provides a wide range of algorithms, along with tools for evaluating the produced recommendations. RELISON includes algorithms and metrics that consider the potential effect of recommendations on the properties of online social networks. For this reason, the library also implements network structure analysis metrics, community detection algorithms, and network diffusion simulation functionalities. The library code and documentation is available at https://github.com/ir-uam/RELISON.

Item Type:Conference Proceedings
Additional Information:This work has been partially funded by the Spanish Government (grant ref. PID2019-108965GB-I00). This work was carried out as part of the Infinitech project which is supported by the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no. 856632.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Sanz-Cruzado Puig, Dr Javier
Authors: Sanz-Cruzado Puig, J., and Castells, P.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
Publisher:ACM
ISBN:9781450387323
Published Online:07 July 2022
Copyright Holders:Copyright © 2022 Copyright is held by the owner/author(s)
First Published:First published in SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval: 2992-3002
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
306194INFINITECHIadh OunisEuropean Commission (EC)856632Computing Science