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NETWORK ANALYSIS

CODE 90530
ACADEMIC YEAR 2019/2020
CREDITS 6 credits during the 1st year of 10852 COMPUTER SCIENCE (LM-18) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR INF/01
LANGUAGE English
TEACHING LOCATION GENOVA (COMPUTER SCIENCE )
SEMESTER 2° Semester
TEACHING MATERIALS AULAWEB

AIMS AND CONTENT

LEARNING OUTCOMES

Learning algorithms and techniques for large scale graph analytics, including centrality measures, connected components, graph clustering, graph properties for random, small-world, and scale free graphs, graph metrics for robustness and resiliency, and graph algorithms for reference problems.

TEACHING METHODS

Lectures, practicals, and individual study.

SYLLABUS/CONTENT

Background on linear algebra and probability.

Complex networks introduction: examples from biology, sociology, economy, computer science.

Network topology (global and local level): connectivity, clustering, centrality measures, diameter, cliques, communities.

Graph models: random graphs, small-world, scale-free networks.

Graphs robustness and fault tolerance.

Web graph: Markov chains and random walk, ranking, search engines.

Dynamic evolution of graphs.

Epidemic models.

Case study: web, social media, epidemic models.

Complex data visualization using open source software tools.

RECOMMENDED READING/BIBLIOGRAPHY

M. E. J. Newman, Networks: An Introduction, Oxford University Press, Oxford (2010)
D. Easley and J. Kleinberg: Networks, Crowds, and Markets: Reasoning About a Highly Connected World (http://www.cs.cornell.edu/home/kleinber/networks-book/)
A. Barabasi: Network Science (http://barabasilab.neu.edu/networksciencebook/)
A. L. Barabasi, Link. La nuova scienza delle reti, Einaudi 2004 , introductory text (optional)

Scientific papers will be suggested during the course.

TEACHERS AND EXAM BOARD

Exam Board

MARINA RIBAUDO (President)

GIORGIO DELZANNO

GIOVANNA GUERRINI

LORENZO ROSASCO

LESSONS

TEACHING METHODS

Lectures, practicals, and individual study.

Class schedule

All class schedules are posted on the EasyAcademy portal.

EXAMS

EXAM DESCRIPTION

Oral examination with discussion of the practicals assigned during the course.

ASSESSMENT METHODS

Individual interview.

Exam schedule

Date Time Location Type Notes
10/01/2020 09:00 GENOVA Esame su appuntamento
10/06/2020 09:00 GENOVA Esame su appuntamento
24/07/2020 09:00 GENOVA Esame su appuntamento
10/09/2020 09:00 GENOVA Esame su appuntamento
18/09/2020 09:00 GENOVA Esame su appuntamento
12/02/2021 09:00 GENOVA Esame su appuntamento