IDENTIFYING DATA

2019_20

Subject (*)

COMPLEX NETWORKS

Code

17685208

Study programme

Computer Security Engineering and Artificial Intelligence (2016)

Cycle

2nd

Descriptors

Credits

Type

Year

Period

Optional

Language

Anglès

Department

Computer Engineering and Mathematics

Coordinator

ARENAS MORENO, ALEJANDRO

GÓMEZ JIMÉNEZ, SERGIO

E-mail

alexandre.arenas@urv.cat
sergio.gomez@urv.cat

Lecturers

ARENAS MORENO, ALEJANDRO

GÓMEZ JIMÉNEZ, SERGIO

Web

General description and relevant information

This course covers the study of the main concepts and algorithms for the analysis of complex networks, the models that summarize their most relevant properties, and the dynamics which take place on top of them. First, we show the presence of complex networks in all kinds of fields (biology, ecology, social sciences, economy, linguistics, etc.) and we analyze their most recurrent and important properties, such as the power law degree distributions, the transitivity, the small world property and the assortativity. We will take special attention to the mesoscopic structure of complex networks, reviewing the main algorithms for the detection of their community structure. We will also study the main models of random complex networks, which allow the understanding of the appearance of their distinctive structural properties. Finally, we will describe some of the dynamics on complex networks, such as synchronization and epidemics spreading.

Competences

Type A	Code	Competences Specific
	A1	Integrate the fundamental technology, applications, services and systems of Computer Security and Artificial Intelligence,in a broader, multidisciplinary context.
	A7	Understand and apply advanced knowledge of high performance computing and numerical or computational problems related to artificial intelligence neural networks and evolutionary systems methods.
	G2	Perform mathematical modelling, calculation and simulation in company technology and engineering centres, particularly in tasks of research, development and innovation in the areas of Computer Security and Artificial Intelligence
Type B	Code	Competences Transversal
	CT1	Become sufficiently independent to work on research projects and scientific or technological collaborations within their thematic area.
	CT2	Forming opinions on the basis of the efficient management and use of information
	CT3	Solve complex problems critically, creatively and innovatively in multidisciplinary contexts.
	CT5	Communicate complex ideas effectively to all sorts of audiences
Type C	Code	Competences Nuclear

Learning outcomes

Type A	Code	Learning outcomes
	A1	Analyse the problems and their causes from a global focus in the medium and long term.
	A7	Know the main characteristics of the complex network theory. Know the structural properties of complex networks. Know how to implement complex network models. Know how to use network community detection methods. Know how to solve dynamic problems in complex networks. Es familiaritza amb la recerca, comprensió i utilització d'articles d'investigació en llengua estrangera.
	G2	Apply the techniques learned in a specific context.
Type B	Code	Learning outcomes
	CT1	Manage and communicate complex information in foreign language.
	CT2	Manage information and knowledge by making efficient use of the information technologies.
	CT3	Recognise the situation as a problem in a multidisciplinary, research or professional environment, and take an active part in finding a solution.
	CT5	Produce a persuasive, consistent and precise discourse that can explain complex ideas and effectively interact with the audience.
Type C	Code	Learning outcomes

Contents

Topic	Sub-topic
Structural properties of complex networks	Introduction to complex networks Real networks examples Classification of networks Metrics on networks
Models of complex networks	Erdos-Renyi model Barabasi-Albert preferential attachment Configuration model Watts-Strogatz small-world model
Mesoscopic description of complex networks	Community structure in complex networks Community detection algorithms Multiple resolution of community structure in networks
Dynamics on networks	Synchronization in complex networks Epidemic spreading in complex networks Other dynamics: percolation, evolutionary games, diffusion, etc.

Planning

Methodologies :: Tests

Competences

(*) Class hours

Hours outside the classroom

(**) Total hours

Introductory activities

Lecture

CT2

IT-based practicals in computer rooms

IT-based practicals

Personal attention

(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies

Methodologies

	Description
Introductory activities	Introduction to the course and its contents
Lecture	Contents exposition and materials availability in electronic form
IT-based practicals in computer rooms	Tools for the developent of solutions and the practical resolution of problems
IT-based practicals	Practical exercises to attain experience and consolidate the theoretical knowledge
Personal attention	Personal tuitition, both in person or through telematic means

Personalized attention

Description

Soving doubts about the contents and practical exercises. Both in person or by email.

Assessment

Methodologies

Competences

Description

Weight

IT-based practicals

Evaluation of practical exercises.

100%

Others


Other comments and second exam session

Sources of information

Basic	Newman, M.E.J., Networks: An Introduction, Oxford University Press, 2010
	Articles in scientific journals: - M.E.J. Newman: The Structure and Function of Complex Networks, SIAM Review 45 (2003) 167–256 - S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, D.-U. Hwang: Complex networks: Structure and dynamics, Physics Reports 424 (2006) 175–308 - S. Fortunato: Community detection in graphs, Physics Reports 486 (2010) 75-174
Complementary

Recommendations

(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.