Description
Date depot: 1 janvier 1900
Titre: Contribution to the modelling and exploitation of large scale social graphs
Directeur de thèse:
Patrick GALLINARI (ISIR (EDITE))
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
The Web 2.0 has changed the perception and the relation the users have with the technologies in general and particularly with all kind of communication means [1]. The user has became the centre of the concerns of the different technologies present on the Web like mashups [2], collaborative environments [3], social networks [4] etc.
From the user’s point of view, this is a precious gift. Despite a low expertise level, a today’s user is able to exchange, create, annotate, etc. network resources.
The approach considering the user in the centre of this process is generating a certain number of interesting challenges theoretical as well as applicative. Thus, there is a consensus that the electronic social networks analysis needs a deep revisit of the existent analysis methods. Indeed, the complexity of this kind of structures, in terms of size, information flow, social networking relations types etc. and technological constraint applying to the electronic resources (e.g.: access rights) reduce the utility of existent methods for the comprehension and deduction of potential interesting phenomenon of these structures.
The traditional approach for studying social networks consists in a graph based modelling of the social relations between users. These relations, implicit or explicit, are calculated based on communications or interactions occurred directly between users or via social resources (e.g. media annotation [7] or using a certain Web service [10]). The main research efforts are focusing on setting new analysis methods (of graphs) or on modifying existent methods to take into account new constraints (e.g. network's size).
In this PhD study a new approach will be investigated in order to obtain a better comprehension and exploitation of social networks. This approach will use hypergraphs [5][6] to model social networks. We are convinced that the links, in general complex to model, between people or resources in social networks, are able to be efficiently exploited only if a representing model capable to capture in a pertinent way their semantic is used.
In addition to that, the use of hypergraphs can help to represent certain relations (e.g. the co-ownership or the relation from a person to several persons) which need additional processing to be exploited.
The final objective of this work is to contribute to the modelling and exploitation of social networks. The PhD study aims to understand the eventual benefit to use hypergraphs in the understanding and exploitation of social networks. The results of this work will be materialized in a set of algorithms dealing with social networks analysis and representative characteristics of these networks.
This work is also related to the indexation and exploitation of the 'deep Web' [8][9].
Several problems of this research topic would be addressed like e.g.:
-# hypergraphs contribution to the modelling of the structure (and semantic) of social networks
-# hypergraphs contribution to a better understand of large scale social networks
-# extracting characteristics of social networks by using hypergraphs models
-# implementing modelling and analysis strategies
[1] T. Berners-Lee, J. Hendler, and O. Lassila. The semantic web. Scientific American, pages 34–43, May 2001.
[2] Giusy Di Lorenzo, Hakim Hacid, Hye-Young Paik, Boualem Benatallah: Data integration in mashups. SIGMOD Record 38(1): 59-66 (2009).
[3] Sihem Amer-Yahia, Jian Huang, Cong Yu: Building community-centric
information exploration applications on social content sites. SIGMOD
Conference 2009: 947-952.
[4] Stanley Wasserman, Katherine Fraust. Social networks analysis: methods and applications. Cambridge University Press. 1994.
[5] Vitaly I. Voloshin. Introduction to Graph and Hypergraph Theory. Nova Science Publishers. 2009. ISBN: 978-1606923726.
[6] Claude Berge. Graphes et Hypergraphes. Dunod. 1973.
[7] Sihem Amer-Yahia, Laks V. S. Lakshmanan, Cong Yu: SocialScope: Enabling Information Discovery on Social Content Sites. CIDR 2009.
[8] Jayant Madhavan, David Ko, Lucja Kot, Vignesh Ganapathy, Alex Rasmussen,Alon Y. Halevy: Google's Deep Web crawl. PVLDB 1(2): 1241-1252 (2008).
[9] Bin He, Mitesh Patel, Zhen Zhang, Kevin Chen-Chuan Chang: Accessing the deep web. Commun. ACM 50(5): 94-101 (2007).
[10] A. Maaradji, H. Hacid, J. Daigremont and N. Crespi. Composition de Services Web Basée sur les Réseau Sociaux. In 10ième Conférence Internationale Francophone sur l'Extraction et la Gestion des Connaissances (EGC2010).
Doctorant.e: Necula Maria Coralia Laura