Giuseppe Manco | Giuseppe Manco

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ARES: Anomaly Recognition Model For Edge Streams
Algorithmic Drift: A simulation framework to study the effects of recommender systems on user preferences
ARES: Anomaly Recognition Model For Edge Streams
Auditing LLM Editorial Bias in News Media Exposure
Breaking domain barriers: mixture of experts for cross-domain fake news detection
Days of Future Past: Towards Robust Detection of Malware Variants via LLM-Based Embedding Generation
Discovering Domain-Agnostic Fake News Detectors Through Deep Self-Supervised Learning
Disrupting Networks: Amplifying Social Dissensus via Opinion Perturbation and Large Language Models
Engagement-Driven Content Generation with Large Language Models
Flexible Generation of Preference Data for Recommendation Analysis
Large language models in the software supply chain: challenges and opportunities
Modeling events and interactions through temporal processes: A survey
Modelling Concept Drift in Dynamic Data Streams for Recommender Systems
On the Feasibility of Android Stegomalware: A Detection Study
Unmasking Conversational Bias in AI Multiagent Systems
A Methodological Approach to Securing Cyber-Physical Systems for Critical Infrastructures
Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferences
Balanced Quality Score: Measuring Popularity Debiasing in Recommendation
Beyond the Horizon: Using Mixture of Experts for Domain Agnostic Fake News Detection
CAP: Detecting Unauthorized Data Usage in Generative Models via Prompt Generation
Dawn of LLM4Cyber: Current Solutions, Challenges, and New Perspectives in Harnessing LLMs for Cybersecurity
Engagement-Driven Content Generation with Large Language Models
GenRec: A Flexible Data Generator for Recommendations
Integrity 2024: Integrity in Social Networks and Media
Link Polarity Prediction from Sparse and Noisy Labels via Multiscale Social Balance
Link Polarity Prediction from Sparse and Noisy Labels via Multiscale Social Balance
LLASP: Fine-tuning Large Language Models for Answer Set Programming
LLASP: Fine-tuning Large Language Models for Answer Set Programming
Relevance Meets Diversity: A User-Centric Framework for Knowledge Exploration Through Recommendations
Relevance meets Diversity: A User-Centric Framework for Knowledge Exploration through Recommendations
Robust anomaly detection via adversarial counterfactual generation
Siamese Networks for Unsupervised Failure Detection in Smart Industry
Special issue on intelligent systems
A federated approach for detecting data hidden in icons of mobile applications delivered via web and multiple stores
Audio-based anomaly detection on edge devices via self-supervision and spectral analysis
Deep Learning/PUF-based Item Identification for Supply Chain Management in a Distributed Ledger Framework
Fighting Misinformation, Radicalization and Bias in Social Media
Integrity 2023: Integrity in Social Networks and Media
Modeling Events and Interactions through Temporal Processes - A Survey
Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels
Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels
Neuro-Symbolic techniques for Predictive Maintenance
ORISHA: Improving Threat Detection through Orchestrated Information Sharing (Discussion Paper)
Siamese Network for Fake Item Detection
Towards Self-Supervised Cross-Domain Fake News Detection
Using AI to face covert attacks in IoT and softwarized scenarios: challenges and opportunities
A Loosely-coupled Neural-symbolic approach to Compliance of Electric Panels
Boosting Cyber-Threat Intelligence via Collaborative Intrusion Detection
Cascade-based Echo Chamber Detection
Cascade-based Echo Chamber Detection
Detection of Network Covert Channels in IoT Ecosystems Using Machine Learning
Detection of Steganographic Threats Targeting Digital Images in Heterogeneous Ecosystems Through Machine Learning
Generating Synthetic Discrete Datasets with Machine Learning
Generative Methods for Out-of-distribution Prediction and Applications for Threat Detection and Analysis: A Short Review
Machine learning methods for generating high dimensional discrete datasets
Revealing MageCart-like Threats in Favicons via Artificial Intelligence
Towards Extreme Multi-Label Classification of Multimedia Content
Hyper-Parameter Optimization for Latent Spaces in Dynamic Recommender Systems
A Deep Learning Approach for Unsupervised Failure Detection in Smart Industry (Discussion Paper)
A Factorization Approach for Survival Analysis on Diffusion Networks
Adversarial Regularized Reconstruction for Anomaly Detection and Generation
Hyper-parameter Optimization for Latent Spaces
Learning Ideological Embeddings from Information Cascades
Sanitization of Images Containing Stegomalware via Machine Learning Approaches
Unbiasing Collaborative Filtering for Popularity-Aware Recommendation (Discussion Paper)
A Deep Learning Approach for Detecting Security Attacks on Blockchain
Deep Autoencoder Ensembles for Anomaly Detection on Blockchain
Exploiting Temporal Convolution for Activity Prediction in Process Analytics
Using an autoencoder in the design of an anomaly detector for smart manufacturing
Deep Learning
Deep Sequential Modeling for Recommendation
Knowledge Discovery in Databases
Network Models
Network Topology
20+ Years of Analytics on Complex Data: Impact, Issues, Challenges and Contributions
Predicting Temporal Activation Patterns via Recurrent Neural Networks
Sequential Variational Autoencoders for Collaborative Filtering
Temporal Recurrent Activation Networks
Differential Privacy and Neural Networks: A Preliminary Analysis
Efficient Methods for Influence-Based Network-Oblivious Community Detection
Fault detection and explanation through big data analysis on sensor streams
Survival Factorization on Diffusion Networks
How Can SMEs Benefit from Big Data? Challenges and a Path Forward
Recent advances in mining patterns from complex data
Rialto: A Knowledge Discovery suite for data analysis
A Generative Bayesian Model for Item and User Recommendation in Social Rating Networks with Trust Relationships
Dealing with trajectory streams by clustering and mathematical transforms
Mining complex patterns
Probabilistic Approaches to Recommendations
Who to follow and why: link prediction with explanations
Cascade-based community detection
Hierarchical clustering of XML documents focused on structural components
Influence-Based Network-Oblivious Community Detection
Outlying Property Detection with Numerical Attributes
Probabilistic topic models for sequence data
Topic-aware social influence propagation models
Towards Topic-aware Social Influence Propagation Models
Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data
Effective Detection of XML Outliers
Effectively Grouping Trajectory Streams
Hierarchical Latent Factors for Preference Data
Probabilistic Sequence Modeling for Recommender Systems
Topic-Aware Social Influence Propagation Models
XML class outlier detection
A Block Coclustering Model for Pattern Discovering in Users' Preference Data
A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data
A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data (Extended Abstract)
An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering
Characterizing Relationships through Co-clustering - A Probabilistic Approach
Data De-duplication: A Review
From global to local and viceversa: uses of associative rule learning for classification in imprecise environments
Modeling item selection and relevance for accurate recommendations: a bayesian approach
A Block Mixture Model for Pattern Discovery in Preference Data
An incremental clustering scheme for data de-duplication
Fast and Effective Hierarchical Clustering of XML Documents by Structure
Mining models of exceptional objects through rule learning
A Hierarchical Rule-based Framework for Accurate Classification in Imprecise Domains
Clustering Relational Data: A Transactional Approach
High Quality True-Positive Prediction for Fiscal Fraud Detection
Rule Learning with Probabilistic Smoothing
SNIPER: A Data Mining Methodology for Fiscal Fraud Detection
A hierarchical model-based approach to co-clustering high-dimensional data
Boosting text segmentation via progressive classification
DAEDALUS: A knowledge discovery analysis framework for movement data
Mining categories for emails via clustering and pattern discovery
Querying and Reasoning for Spatiotemporal Data Mining
The DAEDALUS framework: progressive querying and mining of movement data
A Hierarchical Probabilistic Model for Co-Clustering High-Dimensional Data
Data Mining for Effective Risk Analysis in a Bank Intelligence Scenario
Effective Incremental Clustering for Duplicate Detection in Large Databases
Effective Incremental Clustering for Duplicate Detection in Large Databases
Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data
A Data Mining-based Framework for GridWorkflow Management
An Incremental Clustering Scheme for Duplicate Detection in Large Databases
Exploiting Structural Similarity For Effective Web Information Extraction
Mining and Reasoning on Workflows
Mining Correlations in Workflows Executions
Mining Unconnected Patterns in Workflows
RecBoost: A Supervised Approach to Text Segmentation
A Tree-Based Approach to Clustering XML Documents by Structure
Clustering of XML Documents by Structure based on Tree Matching and Merging
Eureka!: an interactive and visual knowledge discovery tool
Mining Constrained Graphs: The Case of Workflow Systems
Specifying Mining Algorithms with Iterative User-Defined Aggregates
Towards a Logic Query Language for Data Mining
Web wrapper induction: a brief survey
Logical Languages for Data Mining
Mining Frequent Instances on Workflows
Similarity-Based Clustering of Web Transactions
A Framework for Adaptive Mail Classification
Characterizing Web User Accesses: A Transactional Approach to Web Log Clustering
Clustering Transactional Data
Detecting Structural Similarities between XML Documents
Eureka! : A Tool for Interactive Knowledge Discovery
Fast Detection of XML Structural Similarity
LDL-M\(_\mboxine\): Integrating Data Mining with Intelligent Query Answering
Clustering Transactional Data
Data Mining for Intelligent Web Caching
Nondeterministic, Nonmonotonic Logic Databases
Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study
Web log data warehousing and mining for intelligent web caching
Declarative Knowledge Extraction with Interactive User-Defined Aggregates
Making Knowledge Extraction and Reasoning Closer
Experiences with a Logic-Based Knowledge Discovery Support Environment
Experiences with a Logic-based knowledge discovery Support Environment
Integration of Deduction and Induction for Mining Supermarket Sales Data
Querying Inductive Databases via Logic-Based User-Defined Aggregates
Querying inductive Databases via Logic-Based user-defined aggregates
On the Effective Semantics of Nondeterministic, Nonmonotonic, Temporal Logic Databases
Query Answering in Nondeterministic, Nonmonotonic Logic Databases
A Deductive Data Model for Representing and Querying Semistructured Data
Datalog++: A Basis for Active Object-Oriented Databases
Datalog++: a Basis for Active Object.Oriented Databases
Modeling Object Dynamics in Object-Oriented Logic Programming
A Structural (Meta-Logical) Semantics for Linear Objects