print

How the Anti-TrustRank algorithm can help to protect the reputation of financial institutions

author
Astrova, Irina
statement of authorship
Irina Astrova
source
Research Challenges in Information Science : 14th International Conference, RCIS 2020, Limassol, Cyprus, September 23-25, 2020 : Proceedings
location of publication
Cham
publisher
Springer
year of publication
2020
pages
p. 503-508
series
Lecture Notes in Business Information Processing ; 385
conference name, date
14th International Conference, RCIS 2020, September 23-25, 2020
conference location
Limassol, Cyprus
url
https://doi.org/10.1007/978-3-030-50316-1_30
subject term
finantssektor
rahapesu
finantskuriteod
usaldusväärsus
algoritmid
Scopus
Conference proceedings at Scopus
Article at Scopus
WOS
Article at WOS
kvartiil
Q3
category (general)
Business, management and accounting
Decision sciences
Engineering
category (sub)
Business, management and accounting. Business and international management
Business, management and accounting. Management information systems
Decision sciences. Information systems and management
Engineering. Control and systems engineering
keyword
financial institutions
money laundering
terrorist financing
money laundering detection systems
PageRank
TrustRank
Anti-TrustRank
ISBN
978-3-030-50315-4
notes
Bibliogr.: 12 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TTÜ department
tarkvarateaduse instituut
language
inglise
Uurimisrühm
Applied artificial intelligence group
Astrova, I. How the Anti-TrustRank algorithm can help to protect the reputation of financial institutions // Research Challenges in Information Science : 14th International Conference, RCIS 2020, Limassol, Cyprus, September 23-25, 2020 : Proceedings. Cham : Springer, 2020. p. 503-508. (Lecture Notes in Business Information Processing ; 385). https://doi.org/10.1007/978-3-030-50316-1_30