simple example showing how to use biblatex and biber

1. A simple example of how to use “biber” for your
PhD dissertation
Nathalie Villa-Vialaneix
February 3, 2014

2. Contents
1 First chapter
1.1 What I want to explain . . . . . . . . . . . . . . . . . . . . . . .
1.2 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2
2
2
2 Second chapter
3
A Global bibliography
4
B Personal bibliography
6
1

3. Chapter 1
First chapter
1.1
What I want to explain
In this chapter, you cite interesting papers, such as (Newman and Girvan 2004;
Fortunato 2010).
1.2
References
Then, the references corresponding to the first chapter are displayed below.
Fortunato, S. (2010). “Community detection in graphs”. In: Physics Reports
486, pp. 75–174. url: http://arxiv.org/pdf/0906.0612v2.
Newman, M.E.J. and M. Girvan (2004). “Finding and evaluating community
structure in networks”. In: Physical Review, E 69, p. 026113. doi: 10.1103/
PhysRevE.69.026113. url: http://www.citebase.org/abstract?id=
oai%3AarXiv.org%3Acond-mat%2F0308217.
2

4. Chapter 2
Second chapter
In the second chapter, you have other interesting papers, like (Fortunato 2010;
Hammer and Hasenfuss 2010; Boulet et al. 2008).
The corresponding papers (i.e., cited in the second chapter) are listed below.
Boulet, R., B. Jouve, F. Rossi, and N. Villa (2008). “Batch kernel SOM and
related Laplacian methods for social network analysis”. In: Neurocomputing
71.7-9, pp. 1257–1273. doi: doi:10.1016/j.neucom.2007.12.026.
Fortunato, S. (2010). “Community detection in graphs”. In: Physics Reports
486, pp. 75–174. url: http://arxiv.org/pdf/0906.0612v2.
Hammer, B. and A. Hasenfuss (Sept. 2010). “Topographic mapping of large
dissimilarity data sets”. In: Neural Computation 22.9, pp. 2229–2284.
3

5. Appendix A
Global bibliography
This chapter is dedicated to a summary of the cited bibliography.
Bendha¨
ıba, L., M. Olteanu, and N. Villa-Vialaneix (2013). “SOMbrero: cartes
auto-organisatrices stochastiques pour l’int´gration de donn´es d´crites par
e
e
e
des tableaux de dissimilarit´s”. In: 2`mes Rencontres R BoRdeaux. (June 27–
e
e
26, 2013). Lyon, France.
Boulet, R., B. Jouve, F. Rossi, and N. Villa (2008). “Batch kernel SOM and
related Laplacian methods for social network analysis”. In: Neurocomputing
71.7-9, pp. 1257–1273. doi: doi:10.1016/j.neucom.2007.12.026.
Fortunato, S. (2010). “Community detection in graphs”. In: Physics Reports
486, pp. 75–174. url: http://arxiv.org/pdf/0906.0612v2.
Fortunato, S. and M. Barth´l´my (2007). “Resolution limit in community deee
tection”. In: Proceedings of the National Academy of Sciences. Vol. 104. 1.
doi:10.1073/pnas.0605965104; URL: http://www.pnas.org/content/104/
1/36.abstract, pp. 36–41.
Hammer, B., A. Gisbrecht, A. Hasenfuss, B. Mokbel, F.M. Schleif, and X. Zhu
(2011). “Topographic Mapping of Dissimilarity Data”. In: Advances in SelfOrganizing Maps (Proceedings of the 8th Workshop on Self-Organizing Maps,
WSOM 2011). Ed. by J. Laaksonen and T. Honkela. Vol. 6731. Lecture Notes
in Computer Science. Espoo, Finland: Springer, pp. 1–15.
Hammer, B. and A. Hasenfuss (Sept. 2010). “Topographic mapping of large
dissimilarity data sets”. In: Neural Computation 22.9, pp. 2229–2284.
Newman, M.E.J. (2001). “The structure of scientific collaboration networks”.
In: Proceedings of the National Academy of Sciences of the United States of
America 98, p. 0007214. doi: 10.1073pnas.021544898.
— (2002). “Spread of epidemic disease on networks”. In: Physical Review, E
66.016128. doi: 10.1103/PhysRevE.66.016128.
— (2003a). “Mixing patterns in networks”. In: Physical Review, E 67,
p. 026126. doi: 10 . 1103 / PhysRevE . 67 . 026126. url: http : / / prola .
aps.org/abstract/PRE/v67/i2/e026126.
— (2003b). “The structure and function of complex networks”. In: SIAM Review 45, pp. 167–256.
— (2006). “Finding community structure in networks using the eigenvectors of
matrices”. In: Physical Review, E 74.036104. url: http://arxiv.org/abs/
physics/0605087.
4

6. Newman, M.E.J., A.L. Barab´si, and D.J. Watts (2006). The Structure and
a
Dynamics of Networks. Princeton University Press.
Newman, M.E.J. and M. Girvan (2004). “Finding and evaluating community
structure in networks”. In: Physical Review, E 69, p. 026113. doi: 10.1103/
PhysRevE.69.026113. url: http://www.citebase.org/abstract?id=
oai%3AarXiv.org%3Acond-mat%2F0308217.
Newman, M.E.J., D.J. Watts, and S.H. Strogatz (2002). “Random graph models
of social networks”. In: Proceedings of the National Academy of Sciences of
the United States of America 99, pp. 2566–2572.
Olteanu, M. and N. Villa-Vialaneix (2013). “On-line relational and multiple
relational SOM”. In: Neurocomputing. Forthcoming.
Pa¨gelow, M., M.T. Camacho-Olmedo, F. Ferraty, L. Ferr´, P. Sarda, and
e
e
N. Villa (2008). “Modelling Environmental Dynamics”. In: ed. by M.
Pa¨gelow and M.T. Camacho-Olmedo. Environmental Science and Engineere
ing. Berlin/Heidelberg: Springer. Chap. Prospective modelling of environmental dynamics. A methodological comparison applied to mountain land
cover changes, pp. 141–168. isbn: 978-3-540-68489-3.
5

7. Appendix B
Personal bibliography
Boulet, R., B. Jouve, F. Rossi, and N. Villa (2008). “Batch kernel SOM and
related Laplacian methods for social network analysis”. In: Neurocomputing
71.7-9, pp. 1257–1273. doi: doi:10.1016/j.neucom.2007.12.026.
Olteanu, M. and N. Villa-Vialaneix (2013). “On-line relational and multiple
relational SOM”. In: Neurocomputing. Forthcoming.
6