Towards trust inference from bipartite social networks

The emergence of trust as a key link between users in social networks has provided an effective means of enhancing the personalization of online user content. However, the availability of such trust information remains a challenge to the algorithms that use it, as the majority of social networks do not provide a means of explicit trust feedback. This paper presents an investigation into the inference of trust relations between actor pairs of a social network, based solely on the structural information of the bipartite graph typical of most on-line social networks. Using intuition inspired from real life observations, we argue that the popularity of an item in a social graph is inversely related to the level of trust between actor pairs who have rated it. From an existing bipartite social graph, this method computes a new social graph, linking actors together by means of symmetric weighted trust relations. Through a set of experiments performed on a real social network dataset, our method produces statistically significant results, showing strong trust prediction accuracy.

Daire O’Doherty, Salim Jouili, and Peter Van Roy, Towards trust inference in bipartite social networks, proceedings of the 2d ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2012, Scottsdale, USA, ACM, June 2012.

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Hypergraph-based image retrieval for graph-based representation

In this paper, we introduce a novel method for graph indexing. We propose a hypergraph-based model for graph data sets by allowing cluster overlapping. More precisely, in this representation one graph can be assigned to more than one cluster. Using the concept of the graph median and a given threshold, the proposed algorithm detects automatically the number of classes in the graph database. We consider clusters as hyperedges in our hypergraph model and we index the graph set by the hyperedge centroids. This model is interesting to traverse the data set and efficient to retrieve graphs.

Salim Jouili, and Salvatore Tabbone, Hypergraph-based image retrieval for graph-based representation. Journal of the Pattern Recognition Society, April 2012. © 2012 Elsevier Ltd.

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One year of academic research

The R&D Department has been very active this academical year 2010-2011 and has organized research activities in association with many academic organizations such as the Université Libre the Bruxelles (ULB-Belgium), the Université Catholique de Louvain (UCl-Belgium) and the University of Tunis El Manar (Tunisia). These collaborations have taken the form of students Master Theses and Master internships.

In total, four Master Theses have been conducted, with 2 students from the ULB and 2 students from the UCl, along with 3 internships with 2 students from the ULB and 1 student from the enginnering faculty of Tunis. Here is a summary of these work:

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ER 2011: Trends in conceptual modeling researches

This year we published a paper in the industrial track of ER 2011 [1], the annual conference on conceptual modeling research. In this context I spent a couple of days in Brussels at the conference. This gives me the opportunity to share with you an (high level) overview of the trends in this area. Please, notice that this post is only a summary of the discussions I saw and talks I had the chance to see.

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EURA NOVA Publications in 2011

As we usually do at the end of the year,  we will try to summarize the activities led at EURA NOVA R&D during this year. In this post I come back on our scientific publications we had this year. Those publications cover distributed data storage, model management & governance in finance and, finally, elastic architectures for cloud infrastructures. Let me briefly introduce you those papers.

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EURA NOVA selected for the erasmus mundus joint doctorate (EMJD) in distributed computing

The EMJD in Distributed Computing (EMJD-DC) is an international joint doctoral school for the study of distributed computing. EMJD-DC combines a well-structured, interdisciplinary training programme with high-quality research work. The training and research is carried out in cooperation with leading research groups from four universities in different countries: UPC (Spain), KTH (Sweden), IST Lisbon (Portugal), and UCL (Belgium).

Data storage elasticity – quick view on master thesis work (part 1)

Master Theses

In this post I would like to speak about two master theses that EURA NOVA is managing with the Faculty of Science Engineering of the Université Libre de Bruxelles (ULB) and with the Université Catholique de Louvain (UCL).  The two students have been working on the same topic: the elasticity of  data storage on the cloud.  The first cool stuff to notice is that they are working on two different aspects of the elasticity by taking different directions, but at the end of the day, by their two contributions they draw a complete picture of the NoSQL benchmarking in the cloud. In this post I will give you a preview of their work that should be published in June 2011.

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