The twitaholic next door.: scalable friend recommender system using a concept-sensitive hash function

Patrick Bamba (1) , Julien Subercaze (1) , Christophe Gravier (1) , Nabil Benmira (2) , Jimi Fontaine (2)

1 LT2C - Laboratoire Telecom Claude Chappe
2 Graphinium

In this paper we present a Friend Recommender System for micro-blogging. Traditional batch processing of mas- sive amounts of data makes it di cult to provide a near- real time friend recommender system or even a system that can properly scale to millions of users. In order to over- come these issues, we have designed a solution that repre- sents user-generated micro posts as a set of pseudo-cliques. These graphs are assigned a hash value using an original Concept-Sensitive Hash function, a new sub-kind of Locally- Sensitive Hash functions. Finally, since the user pro les are represented as a binary footprint, the pairwise comparison of footprints using the Hamming distance provides scalability to the recommender system. The paper goes with an online application relying on a large Twitter dataset, so that the reader can freely experiment the system.

Mots clés: Locally-Sensitive Hash; Social Networks; Twitter; Friends; Recommender System; Graph; Pseudo-Clique; Locally-Sensitive Hash.

Domaines: Web; Base de données [cs.DB]

Patrick Bamba, Julien Subercaze, Christophe Gravier, Nabil Benmira, Jimi Fontaine. The twitaholic next door.: scalable friend recommender system using a concept-sensitive hash function. ACM International Conference on Information and Knowledge Management, Oct 2012, Hawaii, United States. pp.2275-2278. ⟨hal-00991851⟩