• Publications
  • Influence
Dissecting Ponzi schemes on Ethereum: identification, analysis, and impact
TLDR
We present a comprehensive survey of Ponzi schemes on Ethereum, analysing their behaviour and their impact from various viewpoints. Expand
  • 107
  • 9
  • PDF
Semantics-aware content-based recommender systems: Design and architecture guidelines
TLDR
In this paper we first highlight the current limits in this research area, then we propose design guidelines and an improved architecture to build semantics-aware content-based recommendations. Expand
  • 26
  • 2
  • PDF
Using neural word embeddings to model user behavior and detect user segments
TLDR
We first show the need for a user segmentation system to employ reliable user preferences, since nearly half of the times users reformulate their queries in order to satisfy their information need. Expand
  • 22
  • 1
Evaluating Credit Card Transactions in the Frequency Domain for a Proactive Fraud Detection Approach
TLDR
We propose a novel evaluation criterion based on the analysis, in the frequency domain, of the spectral pattern of the data. Expand
  • 12
  • 1
  • PDF
Forecasting E-Commerce Products Prices by Combining an Autoregressive Integrated Moving Average (ARIMA) Model and Google Trends Data
TLDR
E-commerce is becoming more and more the main instrument for selling goods to the mass market. Expand
  • 12
  • 1
  • PDF
A Discrete Wavelet Transform Approach to Fraud Detection
TLDR
This paper presents a novel fraud detection approach based on the Discrete Wavelet Transform, which is exploited in order to define an evaluation model able to address the aforementioned problems. Expand
  • 15
A semantic approach to remove incoherent items from a user profile and improve the accuracy of a recommender system
TLDR
This paper proposes a novel dynamic coherence-based approach to define the user profile used in the recommender systems, in order to improve the recommendation accuracy. Expand
  • 14
  • PDF
A Frequency-domain-based Pattern Mining for Credit Card Fraud Detection
Nowadays, the prevention of credit card fraud represents a crucial task, since almost all the operators in the E-commerce environment accept payments made through credit cards, aware of that some ofExpand
  • 13
  • PDF
A Linear-dependence-based Approach to Design Proactive Credit Scoring Models
The main aim of a credit scoring model is the classification of the loan customers into two classes, reliable and unreliable customers, on the basis of their potential capability to keep up withExpand
  • 10
  • PDF
Fraud detection for E-commerce transactions by employing a prudential Multiple Consensus model
TLDR
This paper proposes a novel data intelligence technique based on a Prudential Multiple Consensus model which combines the effectiveness of several state-of-the-art classification algorithms by adopting a twofold criterion, probabilistic and majority based. Expand
  • 19
...
1
2
3
4
5
...