Annalisa Appice

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 69

Top Venues

J. Intell. Inf. Syst.

ISMIS

Inf. Sci.

SEBD

Publications

Muhammad Imran, Annalisa Appice, Donato Malerba
Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection. Future Internet 16 (5) (2024)
Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba
PANACEA: a neural model ensemble for cyber-threat detection. Mach. Learn. 113 (8) (2024)
Luca De Rose, Giuseppina Andresini, Annalisa Appice, Donato Malerba
VINCENT: Cyber-threat detection through vision transformers and knowledge distillation. Comput. Secur. 144 (2024)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giuseppe Ieva, Donato Malerba
TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments. J. Intell. Inf. Syst. 62 (3) (2024)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
Enhancing Next Activity Prediction with Adversarial Training of Vision Transformers. SEBD (2024)
Giuseppina Andresini, Annalisa Appice, Donato Malerba
Leveraging Sentinel-2 time series for bark beetle-induced forest dieback inventory. SAC (2024)
Giuseppina Andresini, Annalisa Appice, Dino Ienco, Donato Malerba
SENECA: Change detection in optical imagery using Siamese networks with Active-Transfer Learning. Expert Syst. Appl. 214 (2023)
Filippo Lorè, Pierpaolo Basile, Annalisa Appice, Marco de Gemmis, Donato Malerba, Giovanni Semeraro
An AI framework to support decisions on GDPR compliance. J. Intell. Inf. Syst. 61 (2) (2023)
Giuseppina Andresini, Annalisa Appice, Pasquale Ardimento, Andrea Antonio Brunetta, Antonio Giuseppe Doronzo, Giuseppe Ieva, Francesco Luce, Donato Malerba, Vincenzo Pasquadibisceglie
CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector. AI*IA (2023)
Giuseppina Andresini, Annalisa Appice
Editorial: AI meets cybersecurity. J. Intell. Inf. Syst. 60 (2) (2023)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Nicola Fiorentino, Donato Malerba
STARDUST: A Novel Process Mining Approach to Discover Evolving Models From Trace Streams. IEEE Trans. Serv. Comput. 16 (4) (2023)
Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba
PANACEA: A Neural Model Ensemble for Cyber-Threat Detection. DSAA (2023)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
DARWIN : An online deep learning approach to handle concept drifts in predictive process monitoring. Eng. Appl. Artif. Intell. 123 (Part C) (2023)
Giuseppina Andresini, Annalisa Appice, Donato Malerba
$\mathsf{SILVIA}$: An eXplainable Framework to Map Bark Beetle Infestation in Sentinel-2 Images. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16 (2023)
Giuseppina Andresini, Annalisa Appice, Roberto Gasbarro, Donato Malerba
GLORIA: A Graph Convolutional Network-Based Approach for Review Spam Detection. DS (2023)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Wil M. P. van der Aalst
PROMISE: Coupling predictive process mining to process discovery. Inf. Sci. 606 (2022)
Giuseppina Andresini, Annalisa Appice, Francesco Paolo Caforio, Donato Malerba, Gennaro Vessio
ROULETTE: A neural attention multi-output model for explainable Network Intrusion Detection. Expert Syst. Appl. 201 (2022)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
A Multi-View Deep Learning Approach for Predictive Business Process Monitoring. IEEE Trans. Serv. Comput. 15 (4) (2022)
Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba
XAI to Explore Robustness of Features in Adversarial Training for Cybersecurity. ISMIS (2022)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
A multi-view deep learning approach for predictive business processes monitoring. SERVICES (2022)
Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba
An XAI-based adversarial training approach for cyber-threat detection. DASC/PiCom/CBDCom/CyberSciTech (2022)
Giuseppina Andresini, Annalisa Appice, Daniele Iaia, Donato Malerba, Nicolò Taggio, Antonello Aiello
Leveraging autoencoders in change vector analysis of optical satellite images. J. Intell. Inf. Syst. 58 (3) (2022)
Giuseppina Andresini, Andrea Iovine, Roberto Gasbarro, Marco Lomolino, Marco de Gemmis, Annalisa Appice
Review Spam Detection using Multi-View Deep Learning Combining Content and Behavioral Features. itaDATA (2022)
Giuseppina Andresini, Annalisa Appice, Luca De Rose, Donato Malerba
GAN augmentation to deal with imbalance in imaging-based intrusion detection. Future Gener. Comput. Syst. 123 (2021)
Vincenzo Pasquadibisceglie, Giovanna Castellano, Annalisa Appice, Donato Malerba
FOX: a neuro-Fuzzy model for process Outcome prediction and eXplanation. ICPM (2021)
Annalisa Appice, Angelo Cannarile, Antonella Falini, Donato Malerba, Francesca Mazzia, Cristiano Tamborrino
Leveraging colour-based pseudo-labels to supervise saliency detection in hyperspectral image datasets. J. Intell. Inf. Syst. 57 (3) (2021)
Annalisa Appice, Sergio Escalera, José A. Gámez, Heike Trautmann
Introduction to the special issue of the ECML PKDD 2021 journal track. Mach. Learn. 110 (10) (2021)
Giuseppina Andresini, Feargus Pendlebury, Fabio Pierazzi, Corrado Loglisci, Annalisa Appice, Lorenzo Cavallaro
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection. AISec@CCS (2021)
Annalisa Appice
Keynote 4. SDS (2021)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
Leveraging Multi-view Deep Learning for Next Activity Prediction. ITBPM@BPM (2021)
Giuseppina Andresini, Annalisa Appice, Donato Malerba
Nearest cluster-based intrusion detection through convolutional neural networks. Knowl. Based Syst. 216 (2021)
Francesco Paolo Caforio, Giuseppina Andresini, Gennaro Vessio, Annalisa Appice, Donato Malerba
Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems. DS (2021)
Annalisa Appice
AI meets Cybersecurity. FMEC (2021)
Giuseppina Andresini, Annalisa Appice, Donato Malerba
A Two-Step Network Intrusion Detection System for Multi-Class Classification (Discussion Paper). SEBD (2021)
Malik Al-Essa, Annalisa Appice
Dealing with Imbalanced Data in Multi-class Network Intrusion Detection Systems Using XGBoost. PKDD/ECML Workshops (2) (2021)
Annalisa Appice, Sergio Escalera, José A. Gámez, Heike Trautmann
Introduction to the special issue of the ECML PKDD 2021 journal track. Data Min. Knowl. Discov. 35 (6) (2021)
Giuseppina Andresini, Annalisa Appice, Donato Malerba
Autoencoder-based deep metric learning for network intrusion detection. Inf. Sci. 569 (2021)
Giuseppina Andresini, Annalisa Appice, Corrado Loglisci, Vincenzo Belvedere, Domenico Redavid, Donato Malerba
A Network Intrusion Detection System for Concept Drifting Network Traffic Data. DS (2021)
Giuseppina Andresini, Annalisa Appice, Domenico Dell'Olio, Donato Malerba
Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images. AI*IA (2021)
Annalisa Appice, Giuseppina Andresini, Donato Malerba
Clustering-Aided Multi-View Classification: A Case Study on Android Malware Detection. J. Intell. Inf. Syst. 55 (1) (2020)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba, Giuseppe Modugno
ORANGE: Outcome-Oriented Predictive Process Monitoring Based on Image Encoding and CNNs. IEEE Access 8 (2020)
Antonella Falini, Graziano Castellano, Cristiano Tamborrino, Francesca Mazzia, Rosa Maria Mininni, Annalisa Appice, Donato Malerba
. EAIS (2020)
Annalisa Appice, Francesco Lomuscio, Antonella Falini, Cristiano Tamborrino, Francesca Mazzia, Donato Malerba
Saliency Detection in Hyperspectral Images Using Autoencoder-Based Data Reconstruction. ISMIS (2020)
Annalisa Appice, Yulia R. Gel, Iliyan Iliev, Vyacheslav Lyubchich, Donato Malerba
A Multi-Stage Machine Learning Approach to Predict Dengue Incidence: A Case Study in Mexico. IEEE Access 8 (2020)
Antonella Falini, Cristiano Tamborrino, Graziano Castellano, Francesca Mazzia, Rosa Maria Mininni, Annalisa Appice, Donato Malerba
Novel Reconstruction Errors for Saliency Detection in Hyperspectral Images. LOD (1) (2020)
Annalisa Appice, Pietro Guccione, Emilio Acciaro, Donato Malerba
Detecting salient regions in a bi-temporal hyperspectral scene by iterating clustering and classification. Appl. Intell. 50 (10) (2020)
Annalisa Appice, Pasquale Ardimento, Donato Malerba, Giuseppe Modugno, Diego Marra, Marco Mottola
Training in a Virtual Learning Environment: A Process Mining Approach. EAIS (2020)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
Predictive Process Mining Meets Computer Vision. BPM (Forum) (2020)
Matteo Greco, Michele Spagnoletta, Annalisa Appice, Donato Malerba
Applying Machine Learning to Predict Closing Prices in Stock Market: A Case Study. MIDAS@PKDD/ECML (2020)
Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba
Multi-Channel Deep Feature Learning for Intrusion Detection. IEEE Access 8 (2020)
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba
Using Convolutional Neural Networks for Predictive Process Analytics. ICPM (2019)
Annalisa Appice, Nicola Di Mauro, Francesco Lomuscio, Donato Malerba
Empowering Change Vector Analysis with Autoencoding in Bi-temporal Hyperspectral Images. MACLEAN@PKDD/ECML (2019)
Nicola Di Mauro, Annalisa Appice, Teresa M. A. Basile
Activity Prediction of Business Process Instances with Inception CNN Models. AI*IA (2019)
Annalisa Appice, Nicola Di Mauro, Donato Malerba
Leveraging Shallow Machine Learning to Predict Business Process Behavior. SCC (2019)
Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba
Exploiting the Auto-Encoder Residual Error for Intrusion Detection. EuroS&P Workshops (2019)
Annalisa Appice, Corrado Loglisci, Donato Malerba
Active learning via collective inference in network regression problems. Inf. Sci. (2018)
Annalisa Appice, Antonietta Lanza, Donato Malerba
Wind Speed Forecasting via Structured Output Learning. SEBD (2018)
Sonja Pravilovic, Annalisa Appice, Donato Malerba
Leveraging correlation across space and time to interpolate geophysical data via CoKriging. Int. J. Geogr. Inf. Sci. 32 (1) (2018)
Annalisa Appice, Antonietta Lanza, Donato Malerba
Handling Multi-scale Data via Multi-target Learning for Wind Speed Forecasting. ISMIS (2018)
Annalisa Appice
Towards mining the organizational structure of a dynamic event scenario. J. Intell. Inf. Syst. 50 (1) (2018)
Annalisa Appice, Pietro Guccione, Donato Malerba
A novel spectral-spatial co-training algorithm for the transductive classification of hyperspectral imagery data. Pattern Recognit. 63 (2017)
Sonja Pravilovic, Massimo Bilancia, Annalisa Appice, Donato Malerba
Using multiple time series analysis for geosensor data forecasting. Inf. Sci. 380 (2017)
Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza
Sampling Training Data for Accurate Hyperspectral Image Classification via Tree-Based Spatial Clustering. AI*IA (2017)
Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari
Recent advances in mining patterns from complex data. J. Intell. Inf. Syst. 47 (1) (2016)
Corrado Loglisci, Annalisa Appice, Donato Malerba
Collective regression for handling autocorrelation of network data in a transductive setting. J. Intell. Inf. Syst. 46 (3) (2016)
Annalisa Appice, Pietro Guccione
Exploiting Spatial Correlation of Spectral Signature for Training Data Selection in Hyperspectral Image Classification. DS (2016)
Anna Maria Crespino, Angelo Corallo, Mariangela Lazoi, Donato Barbagallo, Annalisa Appice, Donato Malerba
Anomaly detection in aerospace product manufacturing: Initial remarks. RTSI (2016)
Annalisa Appice, Donato Malerba
A Co-Training Strategy for Multiple View Clustering in Process Mining. IEEE Trans. Serv. Comput. 9 (6) (2016)
Annalisa Appice, Pietro Guccione, Donato Malerba
Transductive hyperspectral image classification: toward integrating spectral and relational features via an iterative ensemble system. Mach. Learn. 103 (3) (2016)
Annalisa Appice, Marco Di Pietro, Claudio Greco, Donato Malerba
Discovering and Tracking Organizational Structures in Event Logs. NFMCP (2015)
Pietro Guccione, Luigi Mascolo, Annalisa Appice
Iterative Hyperspectral Image Classification Using Spectral-Spatial Relational Features. IEEE Trans. Geosci. Remote. Sens. 53 (7) (2015)
Annalisa Appice, Sonja Pravilovic, Antonietta Lanza, Donato Malerba
Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning. Discovery Science (2015)
Annalisa Appice, Anna Ciampi, Donato Malerba
Summarizing numeric spatial data streams by trend cluster discovery. Data Min. Knowl. Discov. 29 (1) (2015)
Fabio Fumarola, Annalisa Appice, Donato Malerba
A Business Intelligence Solution for Monitoring Efficiency of Photovoltaic Power Plants. ISMIS (2014)
Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Elio Masciari, Giuseppe Manco
Mining complex patterns. J. Intell. Inf. Syst. 42 (2) (2014)
Annalisa Appice, Donato Malerba
Leveraging the power of local spatial autocorrelation in geophysical interpolative clustering. Data Min. Knowl. Discov. 28 (5-6) (2014)
Sonja Pravilovic, Annalisa Appice, Donato Malerba
Integrating Cluster Analysis to the ARIMA Model for Forecasting Geosensor Data. ISMIS (2014)
Sonja Pravilovic, Annalisa Appice, Antonietta Lanza, Donato Malerba
Mining Cluster-Based Models of Time Series for Wind Power Prediction. SEBD (2014)
Corrado Loglisci, Annalisa Appice, Donato Malerba
Collective Inference for Handling Autocorrelation in Network Regression. ISMIS (2014)
Annalisa Appice, Michelangelo Ceci, Donato Malerba
Multi-Relational Model Tree Induction Tightly-Coupled with a Relational Database. Fundam. Informaticae 129 (3) (2014)
Annalisa Appice, Pietro Guccione, Donato Malerba, Anna Ciampi
Dealing with temporal and spatial correlations to classify outliers in geophysical data streams. Inf. Sci. 285 (2014)
Sonja Pravilovic, Annalisa Appice, Antonietta Lanza, Donato Malerba
Wind Power Forecasting Using Time Series Cluster Analysis. Discovery Science (2014)
Corrado Loglisci, Annalisa Appice, Antonella Montinari, Donato Malerba
Network Regression in Collective Inference Setting. SEBD (2014)
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski
Dealing with spatial autocorrelation when learning predictive clustering trees. Ecol. Informatics 13 (2013)
Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza
Enhancing Regression Models with Spatio-temporal Indicator Additions. AI*IA (2013)
Sonja Pravilovic, Annalisa Appice, Donato Malerba
Process Mining to Forecast the Future of Running Cases. NFMCP (2013)
Annalisa Appice, Anna Ciampi, Donato Malerba, Pietro Guccione
Using trend clusters for spatiotemporal interpolation of missing data in a sensor network. J. Spatial Inf. Sci. 6 (1) (2013)
Annalisa Appice, Sonja Pravilovic, Donato Malerba
Predictive Regional Trees to Supplement Geo-Physical Random Fields. CORES (2013)
Sonja Pravilovic, Annalisa Appice, Donato Malerba
An Intelligent Technique for Forecasting Spatially Correlated Time Series. AI*IA (2013)
Annalisa Appice, Donato Malerba, Anna Ciampi
Continuously Mining Sliding Window Trend Clusters in a Sensor Network. DEXA (2) (2012)
Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric Paquet, Hongyu Guo
Transductive Relational Classification in the Co-training Paradigm. MLDM (2012)
Pietro Guccione, Anna Ciampi, Annalisa Appice, Donato Malerba, Angelo Muolo
Trend cluster based interpolation everywhere in a sensor network. SAC (2012)
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski
Network regression with predictive clustering trees. Data Min. Knowl. Discov. 25 (2) (2012)
Annalisa Appice, Donato Malerba, Antonietta Lanza
Using Geographic Cost Functions to Discover Vessel Itineraries from AIS Messages. MSM/MUSE (2012)
Anna Ciampi, Annalisa Appice, Pietro Guccione, Donato Malerba
Integrating Trend Clusters for Spatio-temporal Interpolation of Missing Sensor Data. W2GIS (2012)
Anna Ciampi, Annalisa Appice, Donato Malerba, Pietro Guccione
Trend cluster based compression of geographically distributed data streams. CIDM (2011)
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski
Network Regression with Predictive Clustering Trees. ECML/PKDD (3) (2011)
Annalisa Appice, Michelangelo Ceci, Donato Malerba, Antonietta Lanza
Learning and Transferring Geographically Weighted Regression Trees across Time. MSM/MUSE (2011)
Donato Malerba, Michelangelo Ceci, Annalisa Appice
Relational Mining in Spatial Domains: Accomplishments and Challenges. ISMIS (2011)
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski
Global and Local Spatial Autocorrelation in Predictive Clustering Trees. Discovery Science (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Annalisa Appice