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Research Directions For Harvesting Cross-Sectorial Correlations Towards Improved Policy Making

A. Drosou, N. Dimitriou, N. Sarris, A. Konstantinidinis, Dimitrios Tzovaras
2017 Zenodo  
In this context,a multi-purpose platform for data analytics is briefly exhibited in order to demonstrate the potential of such approaches to policy making.  ...  To this direction, modern technologies like data mining, data and visual analytics, artificial intelligence, etc. can be of significant value, if offering a comprehensive communication of potentially useful  ...  The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of the European Commission.  ... 
doi:10.5281/zenodo.571543 fatcat:3nuk2xamqnhnbf7krt5d2vkll4

Rule-based Blockchain Knowledge Graphs: Declarative AI for Solving Industrial Blockchain Challenges

Luigi Bellomarini, Giuseppe Galano, Markus Nissl, Emanuel Sallinger
2021 International Web Rule Symposium  
In this paper, we report on an international industrial and academic collaboration that uses a declarative, rule-based approach on top of a Knowledge Graph system and describes the use-case of analyzing  ...  There is a clear industrial need to bring together many of those valuable methods into a principled approach that upholds central aspects such as the ability to provide explainable analytics.  ...  Acknowledgements The financial support by the Vienna Science and Technology Fund (WWTF) grant VRG18-013 is gratefully acknowledged.  ... 
dblp:conf/ruleml/BellomariniGNS21 fatcat:a5s6zys3z5cbplqp5wrppexcuu

Visual analytics for loan guarantee network risk management [article]

Dawei Cheng, Zhibin Niu, Junchi Yan, Jiawan Zhang, Liqing Zhang
2017 arXiv   pre-print
interactive approach is presented; iii) visual analytics for high defaults pattern, whereby a motif detection based interactive approach is described, and we adopt a Shneiderman Mantra strategy to reduce  ...  the computation complexity. iv) visual analytics for evolving guarantee network, whereby animation is used to help understanding the guarantee dynamic; v) visual analytics approach and interface for default  ...  Anomalous and significant subgraphs in social network can be used for early detection of emerging events such as civil unrest prediction, rare disease outbreak detection, and early detection of human rights  ... 
arXiv:1705.02937v1 fatcat:q5zxwf6bgbce3afu7gkco44ifi

Visual Analytics of Twitter and Social Media Dataflows: a Casestudy of COVID-19 Rumors

M.S. Ulizko, E.V. Antonov, M. A. Grigorieva, E.S. Tretyakov, R.R. Tukumbetova, A.A. Artamonov
2021 Scientific Visualization  
The study was conducted with the use of web scraping, methods of linguistic analysis and visual analytics.  ...  The solving of such problems is daunting due to the global growth of the amount of information and its availability for a wide range of users.  ...  The used visualisation methods in the developed web-application for Twitter analysis enables to detect events that cause public resonance and are discussed by the society.  ... 
doi:10.26583/sv.13.4.11 fatcat:ffo2xhdjdnabvdzhot6wih6yua

AI in Finance: Challenges, Techniques and Opportunities [article]

Longbing Cao
2021 arXiv   pre-print
We then structure and illustrate the data-driven analytics and learning of financial businesses and data.  ...  In contrast to either discussing the problems, aspects and opportunities of finance that have benefited from specific AI techniques and in particular some new-generation AI and data science (AIDS) areas  ...  Such information can be used for different financial engineering, economic computing, quantitative analysis, data-driven analytics, and decision-support purposes and tasks.  ... 
arXiv:2107.09051v1 fatcat:g62cz4dqt5dcrbckn4lbveat3u

Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensics [article]

Nadia Pocher, Mirko Zichichi, Fabio Merizzi, Muhammad Zohaib Shafiq, Stefano Ferretti
2022 arXiv   pre-print
The rise of blockchain and distributed ledger technologies (DLTs) in the financial sector has generated a socio-economic shift that triggered legal concerns and regulatory initiatives.  ...  After providing some background on the notion of anonymity in the IoM and on the interplay between AML/CFT and blockchain forensics, we focus on anomaly detection approaches leading to our experiments.  ...  Acknowledgements The contribution of Nadia Pocher and Mirko Zichichi received funding from the EU H2020 research and innovation programme under the MSCA ITN European Joint Doctorate grant agreement No  ... 
arXiv:2206.04803v1 fatcat:35ik44ftpzde5bmv5pmq6yo37e

The impact of word sense disambiguation on stock price prediction

Alexander Hogenboom, Alex Brojba-Micu, Flavius Frasincar
2021 Expert systems with applications  
The number of detected events tends to reduce with over 30% when graph-based word sense disambiguation using a degree centrality measure is applied in the event detection process, thus reducing the noise  ...  We identify events in natural language news messages and subsequently weight these events for their historical impact on stock prices.  ...  In more recent work, Nuij et al. (2014) detect financial events in large amounts of news messages and subsequently use these events in order to determine whether to buy or sell stocks for companies of  ... 
doi:10.1016/j.eswa.2021.115568 fatcat:ojssxqawwng4rofv7wojzwqgoy

Mining Unstructured Turkish Economy News Articles

Esra Kahya Özyirmidokuz
2014 Procedia Economics and Finance  
Text mining allows us to analyze web content dynamically to find meaningful patterns within large collections of textual data. There are too many economic news articles to read.  ...  In addition, k-means clustering is used. Consequently, the clusters and similarities of the articles are obtained.  ...  Besides identifying events and presenting news titles and keywords that the topic detection and tracking techniques are used to do, a summarized text to present event evolution is necessary for general  ... 
doi:10.1016/s2212-5671(14)00809-0 fatcat:owg4kjjnerbsfpwnmngteljnn4

Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case

Andreas Alexopoulos, Yolanda Becerra, Omer Boehm, George Bravos, Vasilis Chatzigiannakis, Cesare Cugnasco, Giorgos Demetriou, Iliada Eleftheriou, Lidija Fodor, Spiros Fotis, Sotiris Ioannidis, Dusan Jakovetic (+18 others)
2021 Zenodo  
For each use case, we present the architecture, data analysis and visualization provided by the I-BiDaaS solution, reporting on the achieved results, domain-specific impact, and lessons learned.  ...  In order to harness value from such high-volume and high-variety of data, banks need to resolve several challenges, such as finding efficient ways to perform Big Data analytics and to provide solutions  ...  Acknowledgements The research presented in this book chapter was undertaken in the framework of the I-BiDaaS project ("Industrial-Driven Big Data as a Self-Service Solution") funded by the Horizon 2020  ... 
doi:10.5281/zenodo.4540175 fatcat:adm2jhaprbdaxa4dq6byf2cbwu

Detecting and Preventing Fraud with Data Analytics

Adrian Bănărescu
2015 Procedia Economics and Finance  
Fraud involves inclusively significant financial risks which may threaten profitability, and the image of an economic entity.  ...  Such new and significant information will be later used in directing investigations, as well as to make recommendations to improve the control activities.  ...  This project is co-financed by European Social Fund through Sectoral Operational Programme for Human Resources Development 2007-2013. Investing in people!  ... 
doi:10.1016/s2212-5671(15)01485-9 fatcat:eglgqnlydrgt3av63woghr2ieu

Anchoring AI/Machine Learning on the African Technological Innovation and Investment Table

Gabriel Kabanda, Secretary General, Zimbabwe Academy of Sciences, TREP Building, University of Zimbabwe, Harare, ZIMBABWE
2021 The business & management review: Conference Proceedings  
Machine Learning (ML) entails the automatic data analysis of large data sets and production of models for the general relationships found among data.  ...  The research used the KDDCup 1999 intrusion detection benchmark dataset in order to build an efficient network intrusion detection system.  ...  eigenvectors and convergence of graph attributes to find the patterns, respectively. 3) Community-based approaches: the main action in these approaches is graph clustering where the clustering algorithms  ... 
doi:10.24052/bmr/v12nu02/art-07 fatcat:ejt57omxdra6lbmulwrhzkfyrm

Using social network analysis to prevent money laundering

Andrea Fronzetti Colladon, Elisa Remondi
2017 Expert systems with applications  
Our findings show the importance of using a network-based approach when looking for suspicious financial operations and potential criminals.  ...  We propose a new approach to sort and map relational data and present predictive models, based on network metrics, to assess risk profiles of clients involved in the factoring business.  ...  Acknowledgements We are grateful to Donato Franco, Senior Manager at KPMG Spa, for sharing his knowledge about anti-money laundering regulations in Italy and their practical applications.  ... 
doi:10.1016/j.eswa.2016.09.029 fatcat:ct7265nq55dhjo4x3xhdc55zua

Connecting The Dots To Combat Collective Fraud [article]

Mingxi Wu, Xi Chen
2021 arXiv   pre-print
We show that with TigerGraph, a powerful graph database, and its innovative query language - GSQL, data scientists and fraud experts can conveniently implement and deploy an end-to-end risk control system  ...  as a graph database application.  ...  Analytical Queries The analytic query we use is to cluster accounts into CCs using the shared_ip co-context edges.  ... 
arXiv:2101.01898v1 fatcat:zwaalavukze5jbrsl5ko4av52e

Advances in GMDH-based Predictive Analytics Tools for Business Intelligence Systems

Serhiy Yefimenko
2018 International Conference on Advanced Computer Information Technologies  
Contemporary tools of predictive analytics, used for effective making of business decisions, are considered. The concept of advanced GMDH-based predictive analytics tool is proposed.  ...  The paper analyzes approaches to prediction of economic processes in business intelligence systems.  ...  The purpose of the review is to consider modern approaches to prediction economic, production and financial processes in BI systems, as well as existing software tools for predictive analytics. II.  ... 
dblp:conf/acit4/Yefimenko18 fatcat:nomf7xwuifb2bct3jivnbh36xa

Predictive Modeling for Optimization of Field Operations in Bike-Sharing Systems

Simon Ruffieux, Elena Mugellini, Omar Abou Khaled
2019 2019 6th Swiss Conference on Data Science (SDS)  
Kaspar Mösinger, Raiffeisen @ARENA Fraud Detection in Financial Services Using Graph Analysis and Machine Learning Both graph analysis and machine learning can be used very effectively to detect anomalies  ...  How does PwC approach data and analytics?  ... 
doi:10.1109/sds.2019.00011 dblp:conf/sds2/RuffieuxMK19 fatcat:z5bcj6f2pjczvbwp4zooavn6ve
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