Demir Benan

Curriculum
Neuroscience, Technology, and Society, XXXII series
Grant sponsor

CARIPARO
Supervisor

Anna Spagnolli
Co-supervisor
GianAntonio Susto

Fastelli Ambra

Curriculum
Neuroscience, Technology, and Society, XXXII series
Grant sponsor

FBK
Supervisor

Barbara Arfè
Co-supervisor
Ornella Mich (FBK)
Contact
ambra.fastelli[at]phd.unipd.it

Terzi Matteo

Curriculum
Computer Science and Innovation for Societal Challenges, XXXII series
Grant sponsor
FBK
Supervisor

GianAntonio Susto
Co-supervisors
Luciano Serafini, Luciano Gamberini
Contact

Montemurro Sonia

Curriculum
Neuroscience, Technology, and Society, XXXII series
Grant sponsor

UNIPD
Supervisor

Sara Mondini
Co-supervisor
Ombretta Gaggi
Contact
sonia.montemurro[at]studenti.unipd.it

Rabbani Md Masoom

Curriculum
Computer Science and Innovation for Societal Challenges, XXXII series
Grant sponsor
FBK
Supervisor

Mauro Conti
Co-supervisors

Moret Beatrice

Curriculum
Neuroscience, Technology, and Society, XXXII series
Grant sponsor

UNIPD
Supervisor

Gianluca Campana
Co-supervisor
Claudio Enrico Palazzi
Contact
beatrice.moret[at]studenti.unipd.it

Padoan Tommaso

Curriculum
Computer Science and Innovation for Societal Challenges, XXXII series
Grant sponsor
UNIPD
Supervisor

Paolo Baldan
Co-supervisor
Sara Mondini
Contact

Sacchi Chiara

Curriculum
Neuroscience, Technology, and Society, XXXII series
Grant sponsor

UNIPD
Supervisor

Alessandra Simonelli
Co-supervisor
Fabio Aiolli
Contact
chiara.sacchi[at]studenti.unipd.it

Chiara Masiero

Name and surname
Chiara Masiero

Contacts
Human Inspired Technology Research Centre
Via Venezia, 8 - 35121 Padova, Italy.
Mail: chiara.masiero[at]unipd.it

Research interests
The core topic of my research activity is Sentiment analysis, whose aim is determining the attitude of a writer in a document by means of Machine Learning techniques.
Sentiment analysis is widely applied to the monitoring of web and social media contents.

FRAUD DETECTION BASED ON CREDIT CARD TRANSACTIONS AND ON-LINE USER BEHAVIOUR

On-line payment methodologies are subjected to fraud and identity theft. Providers of payment systems have set up heuristic criteria based on experience to flag and stop suspected transactions; however, the current state-of-the-art has two main flaws:
- Fraudsters are generally able to find out new ways to bypass the newly adopted system restrictions and therefore new frauds typology may not be detected;

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