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Balancing Act: Tackling organized retail fraud on e-commerce platforms with imbalanced learning text models
Abed Mutemi
,
Fernando Bação
Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
Research output
:
Contribution to journal
›
Article
›
peer-review
3
Citations (Scopus)
29
Downloads (Pure)
Overview
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Dive into the research topics of 'Balancing Act: Tackling organized retail fraud on e-commerce platforms with imbalanced learning text models'. Together they form a unique fingerprint.
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Business & Economics
Retail
98%
Fraud
85%
Electronic Commerce
68%
Fraud Detection
57%
Classifier
51%
Online Shopping
44%
Data Augmentation
33%
Knowledge Extraction
32%
Learning Model
32%
Retailers
29%
Model Evaluation
29%
Machine Learning
28%
Best Practice
27%
Learning Algorithm
26%
Key Words
23%
Crime
23%
Federation
22%
Performance
8%
Costs
8%
Social Sciences
electronic business
100%
fraud
89%
act
58%
learning
29%
federation
17%
sales
16%
best practice
13%
offense
11%
costs
9%
performance
8%
evaluation
7%
Engineering & Materials Science
Classifiers
61%
Crime
52%
Knowledge representation
47%
Random forests
45%
Sales
41%
Learning algorithms
36%
Machine learning
31%
Costs
16%