Probabilistic Graphical Model for the Web

The world wide web network is a network with a
complex topology, the main properties of which are the distribution
of degrees in power law, A low clustering coefficient and a weak
average distance. Modeling the web as a graph allows locating the
information in little time and consequently offering a help in the
construction of the research engine. Here, we present a model based
on the already existing probabilistic graphs with all the aforesaid
characteristics. This work will consist in studying the web in order to
know its structuring thus it will enable us to modelize it more easily
and propose a possible algorithm for its exploration.

• M. Nekri
• A. Khelladi

• Clustering coefficient
• preferential attachment
• small world
• Web community.

[1] P. Baldi, P.Frasconi and P.Smyth, “Modeling the Internet and the web,
Probabilistic Methods and Algorithms,” John Wiley and Sons, Ltd,
Chichester, West Sussex, England, 2003.
[2] A.L. Barabasi, R. Albert, “Emergence of scaling in random networks,”
Science 286, 1999, pp.509–512.
[3] A.L. Barabasi, R. Albert, H. Jeong and G. Bianconi, “Power-law
distribution of the World Wide Web,” Science 287(2115), 2000.
[4] A. Broder, F. Kumer, S. Rajagopalan et all, “Graph structure in the
Web,” Computer Networks 33, 2000, pp.309–320.
[5] A. Bonato, “A survey of models of the web graph,” Proceedings of
Combinatorial and Algorithmic Aspects of Networking, 2004.
[6] J.L. Guillaume, M. Latapy, “Topologie d’Internet et de Web: mesure et
modélisation,” Actes du premier colloque Mesures de l’Internet, Nice,
France, 2003.
[7] J.L. Guillaume, “Analyse statistique et modélisation des grands réseaux”
PhD Thesis, Paris 7 university, France, 2004.
[8] M. Lyckova, I. Charon, L. et all. (2005), “Rapport sur le projet WEBMOPT
Optimisation et modélisation du graphe du Web,” Département
Informatique et réseaux. Groupe Mathématiques de l’Informatique et des
réseaux.
[9] P.Pons, “Détection de communautés dans les grands graphes de
terrain, ”PhD Thesis, Paris 7 university, France, 2007.
[10] D. Watts and S. Strogatz “Collective Dynamics of Small-World
Networks,” Nature 393, 1998, pp 440-442.