Annalisa Appice

Orcid: 0000-0001-9840-844X

Affiliations:
  • University of Bari Aldo Moro, Italy


According to our database1, Annalisa Appice authored at least 167 papers between 2001 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
An AI framework to support decisions on GDPR compliance.
J. Intell. Inf. Syst., October, 2023

Editorial: AI meets cybersecurity.
J. Intell. Inf. Syst., April, 2023

STARDUST: A Novel Process Mining Approach to Discover Evolving Models From Trace Streams.
IEEE Trans. Serv. Comput., 2023

$\mathsf{SILVIA}$: An eXplainable Framework to Map Bark Beetle Infestation in Sentinel-2 Images.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

SENECA: Change detection in optical imagery using Siamese networks with Active-Transfer Learning.
Expert Syst. Appl., 2023

DARWIN : An online deep learning approach to handle concept drifts in predictive process monitoring.
Eng. Appl. Artif. Intell., 2023

PANACEA: A Neural Model Ensemble for Cyber-Threat Detection.
Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

GLORIA: A Graph Convolutional Network-Based Approach for Review Spam Detection.
Proceedings of the Discovery Science - 26th International Conference, 2023

CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector.
Proceedings of the AIxIA 2023 - Advances in Artificial Intelligence, 2023

2022
A Multi-View Deep Learning Approach for Predictive Business Process Monitoring.
IEEE Trans. Serv. Comput., 2022

Leveraging autoencoders in change vector analysis of optical satellite images.
J. Intell. Inf. Syst., 2022

PROMISE: Coupling predictive process mining to process discovery.
Inf. Sci., 2022

ROULETTE: A neural attention multi-output model for explainable Network Intrusion Detection.
Expert Syst. Appl., 2022

A multi-view deep learning approach for predictive business processes monitoring.
Proceedings of the IEEE World Congress on Services, 2022

Review Spam Detection using Multi-View Deep Learning Combining Content and Behavioral Features.
Proceedings of the 1st Italian Conference on Big Data and Data Science (itaDATA 2022), 2022

XAI to Explore Robustness of Features in Adversarial Training for Cybersecurity.
Proceedings of the Foundations of Intelligent Systems - 26th International Symposium, 2022

An XAI-based adversarial training approach for cyber-threat detection.
Proceedings of the IEEE Intl. Conf. on Dependable, 2022

2021
Nearest cluster-based intrusion detection through convolutional neural networks.
Knowl. Based Syst., 2021

Leveraging colour-based pseudo-labels to supervise saliency detection in hyperspectral image datasets.
J. Intell. Inf. Syst., 2021

Autoencoder-based deep metric learning for network intrusion detection.
Inf. Sci., 2021

GAN augmentation to deal with imbalance in imaging-based intrusion detection.
Future Gener. Comput. Syst., 2021

Introduction to the special issue of the ECML PKDD 2021 journal track.
Data Min. Knowl. Discov., 2021

A Two-Step Network Intrusion Detection System for Multi-Class Classification (Discussion Paper).
Proceedings of the 29th Italian Symposium on Advanced Database Systems, 2021

Keynote 4.
Proceedings of the Eighth International Conference on Software Defined Systems, 2021

Dealing with Imbalanced Data in Multi-class Network Intrusion Detection Systems Using XGBoost.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

FOX: a neuro-Fuzzy model for process Outcome prediction and eXplanation.
Proceedings of the 3rd International Conference on Process Mining, 2021

AI meets Cybersecurity.
Proceedings of the Sixth International Conference on Fog and Mobile Edge Computing, 2021

Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems.
Proceedings of the Discovery Science - 24th International Conference, 2021

A Network Intrusion Detection System for Concept Drifting Network Traffic Data.
Proceedings of the Discovery Science - 24th International Conference, 2021

INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection.
Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

Leveraging Multi-view Deep Learning for Next Activity Prediction.
Proceedings of the 1st Italian Forum on Business Process Management co-located with the 19th International Conference of Business Process Management (BPM 2021), 2021

Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images.
Proceedings of the AIxIA 2021 - Advances in Artificial Intelligence, 2021

2020
Dealing with Class Imbalance in Android Malware Detection by Cascading Clustering and Classification.
Proceedings of the Complex Pattern Mining - New Challenges, Methods and Applications, 2020

Clustering-Aided Multi-View Classification: A Case Study on Android Malware Detection.
J. Intell. Inf. Syst., 2020

Detecting salient regions in a bi-temporal hyperspectral scene by iterating clustering and classification.
Appl. Intell., 2020

ORANGE: Outcome-Oriented Predictive Process Monitoring Based on Image Encoding and CNNs.
IEEE Access, 2020

A Multi-Stage Machine Learning Approach to Predict Dengue Incidence: A Case Study in Mexico.
IEEE Access, 2020

Multi-Channel Deep Feature Learning for Intrusion Detection.
IEEE Access, 2020

Applying Machine Learning to Predict Closing Prices in Stock Market: A Case Study.
Proceedings of the Mining Data for Financial Applications - 5th ECML PKDD Workshop, 2020

Novel Reconstruction Errors for Saliency Detection in Hyperspectral Images.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Saliency Detection in Hyperspectral Images Using Autoencoder-Based Data Reconstruction.
Proceedings of the Foundations of Intelligent Systems - 25th International Symposium, 2020

Saliency Detection for Hyperspectral Images via Sparse-Non Negative-Matrix-Factorization and novel Distance Measures<sup>*</sup>.
Proceedings of the 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2020

Training in a Virtual Learning Environment: A Process Mining Approach.
Proceedings of the 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2020

Predictive Process Mining Meets Computer Vision.
Proceedings of the Business Process Management Forum, 2020

2019
Empowering Change Vector Analysis with Autoencoding in Bi-temporal Hyperspectral Images.
Proceedings of MACLEAN: MAChine Learning for EArth ObservatioN Workshop co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2019), 2019

Using Convolutional Neural Networks for Predictive Process Analytics.
Proceedings of the International Conference on Process Mining, 2019

Exploiting the Auto-Encoder Residual Error for Intrusion Detection.
Proceedings of the 2019 IEEE European Symposium on Security and Privacy Workshops, 2019

Activity Prediction of Business Process Instances with Inception CNN Models.
Proceedings of the AI*IA 2019 - Advances in Artificial Intelligence, 2019

Leveraging Shallow Machine Learning to Predict Business Process Behavior.
Proceedings of the 2019 IEEE International Conference on Services Computing, 2019

2018
Towards mining the organizational structure of a dynamic event scenario.
J. Intell. Inf. Syst., 2018

Active learning via collective inference in network regression problems.
Inf. Sci., 2018

Leveraging correlation across space and time to interpolate geophysical data via CoKriging.
Int. J. Geogr. Inf. Sci., 2018

Wind Speed Forecasting via Structured Output Learning.
Proceedings of the 26th Italian Symposium on Advanced Database Systems, 2018

Handling Multi-scale Data via Multi-target Learning for Wind Speed Forecasting.
Proceedings of the Foundations of Intelligent Systems - 24th International Symposium, 2018

Relational Data Mining in the Era of Big Data.
Proceedings of the A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years., 2018

2017
A novel spectral-spatial co-training algorithm for the transductive classification of hyperspectral imagery data.
Pattern Recognit., 2017

Using multiple time series analysis for geosensor data forecasting.
Inf. Sci., 2017

Sampling Training Data for Accurate Hyperspectral Image Classification via Tree-Based Spatial Clustering.
Proceedings of the AI*IA 2017 Advances in Artificial Intelligence, 2017

2016
A Co-Training Strategy for Multiple View Clustering in Process Mining.
IEEE Trans. Serv. Comput., 2016

Transductive hyperspectral image classification: toward integrating spectral and relational features via an iterative ensemble system.
Mach. Learn., 2016

Collective regression for handling autocorrelation of network data in a transductive setting.
J. Intell. Inf. Syst., 2016

Recent advances in mining patterns from complex data.
J. Intell. Inf. Syst., 2016

Anomaly detection in aerospace product manufacturing: Initial remarks.
Proceedings of the 2nd IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow, 2016

Exploiting Spatial Correlation of Spectral Signature for Training Data Selection in Hyperspectral Image Classification.
Proceedings of the Discovery Science - 19th International Conference, 2016

2015
Iterative Hyperspectral Image Classification Using Spectral-Spatial Relational Features.
IEEE Trans. Geosci. Remote. Sens., 2015

Summarizing numeric spatial data streams by trend cluster discovery.
Data Min. Knowl. Discov., 2015

Discovering and Tracking Organizational Structures in Event Logs.
Proceedings of the New Frontiers in Mining Complex Patterns - 4th International Workshop, 2015

Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning.
Proceedings of the Discovery Science - 18th International Conference, 2015

2014
Mining complex patterns.
J. Intell. Inf. Syst., 2014

Dealing with temporal and spatial correlations to classify outliers in geophysical data streams.
Inf. Sci., 2014

Multi-Relational Model Tree Induction Tightly-Coupled with a Relational Database.
Fundam. Informaticae, 2014

Leveraging the power of local spatial autocorrelation in geophysical interpolative clustering.
Data Min. Knowl. Discov., 2014

Mining Cluster-Based Models of Time Series for Wind Power Prediction.
Proceedings of the 22nd Italian Symposium on Advanced Database Systems, 2014

Network Regression in Collective Inference Setting.
Proceedings of the 22nd Italian Symposium on Advanced Database Systems, 2014

Integrating Cluster Analysis to the ARIMA Model for Forecasting Geosensor Data.
Proceedings of the Foundations of Intelligent Systems - 21st International Symposium, 2014

Collective Inference for Handling Autocorrelation in Network Regression.
Proceedings of the Foundations of Intelligent Systems - 21st International Symposium, 2014

A Business Intelligence Solution for Monitoring Efficiency of Photovoltaic Power Plants.
Proceedings of the Foundations of Intelligent Systems - 21st International Symposium, 2014

Wind Power Forecasting Using Time Series Cluster Analysis.
Proceedings of the Discovery Science - 17th International Conference, 2014

Data Mining Techniques in Sensor Networks - Summarization, Interpolation and Surveillance.
Springer Briefs in Computer Science, Springer, ISBN: 978-1-4471-5453-2, 2014

2013
Using trend clusters for spatiotemporal interpolation of missing data in a sensor network.
J. Spatial Inf. Sci., 2013

Dealing with spatial autocorrelation when learning predictive clustering trees.
Ecol. Informatics, 2013

Process Mining to Forecast the Future of Running Cases.
Proceedings of the New Frontiers in Mining Complex Patterns, 2013

Predictive Regional Trees to Supplement Geo-Physical Random Fields.
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, 2013

An Intelligent Technique for Forecasting Spatially Correlated Time Series.
Proceedings of the AI*IA 2013: Advances in Artificial Intelligence, 2013

Enhancing Regression Models with Spatio-temporal Indicator Additions.
Proceedings of the AI*IA 2013: Advances in Artificial Intelligence, 2013

2012
Network regression with predictive clustering trees.
Data Min. Knowl. Discov., 2012

Integrating Trend Clusters for Spatio-temporal Interpolation of Missing Sensor Data.
Proceedings of the Web and Wireless Geographical Information Systems, 2012

Trend cluster based interpolation everywhere in a sensor network.
Proceedings of the ACM Symposium on Applied Computing, 2012

Using Geographic Cost Functions to Discover Vessel Itineraries from AIS Messages.
Proceedings of the Ubiquitous Social Media Analysis, 2012

Transductive Relational Classification in the Co-training Paradigm.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2012

Continuously Mining Sliding Window Trend Clusters in a Sensor Network.
Proceedings of the Database and Expert Systems Applications, 2012

2011
A parallel, distributed algorithm for relational frequent pattern discovery from very large data sets.
Intell. Data Anal., 2011

Trend Cluster Based Kriging Interpolation in Sensor Data Networks.
Proceedings of the Modeling and Mining Ubiquitous Social Media, 2011

Learning and Transferring Geographically Weighted Regression Trees across Time.
Proceedings of the Modeling and Mining Ubiquitous Social Media, 2011

Relational Disjunctive Patterns Mining for Discovering Frequent Variants in Process Models.
Proceedings of the Sistemi Evoluti per Basi di Dati, 2011

Relational Mining in Spatial Domains: Accomplishments and Challenges.
Proceedings of the Foundations of Intelligent Systems - 19th International Symposium, 2011

Space-Time Roll-up and Drill-down into Geo-Trend Stream Cubes.
Proceedings of the Foundations of Intelligent Systems - 19th International Symposium, 2011

MBlab: Molecular Biodiversity Laboratory.
Proceedings of the Digital Libraries and Archives - 7th Italian Research Conference, 2011

Global and Local Spatial Autocorrelation in Predictive Clustering Trees.
Proceedings of the Discovery Science - 14th International Conference, 2011

Discovering process models through relational disjunctive patterns mining.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2011

Trend cluster based compression of geographically distributed data streams.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2011

2010
Transductive Learning for Spatial Data Classification.
Proceedings of the Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S. Michalski, 2010

Clustering Spatio-Temporal Data Streams.
Proceedings of the Eighteenth Italian Symposium on Advanced Database Systems, 2010

Suggesting Tourist Destinations by means of Time-Slice Density Estimation.
Proceedings of the Eighteenth Italian Symposium on Advanced Database Systems, 2010

Complex objects ranking: a relational data mining approach.
Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), 2010

Transductive learning for spatial regression with co-training.
Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), 2010

Summarization for Geographically Distributed Data Streams.
Proceedings of the Knowledge-Based and Intelligent Information and Engineering Systems, 2010

Online and Offline Trend Cluster Discovery in Spatially Distributed Data Streams.
Proceedings of the Analysis of Social Media and Ubiquitous Data, 2010

Time-Slice Density Estimation for Semantic-Based Tourist Destination Suggestion.
Proceedings of the ECAI 2010, 2010

Discovering Informative Syntactic Relationships between Named Entities in Biomedical Literature.
Proceedings of the Second International Conference on Advances in Databases, 2010

2009
A relational approach to probabilistic classification in a transductive setting.
Eng. Appl. Artif. Intell., 2009

Mining preference relations to rank complex object.
Proceedings of the Seventeenth Italian Symposium on Advanced Database Systems, 2009

Spatial Regression in the Transductive Setting.
Proceedings of the Seventeenth Italian Symposium on Advanced Database Systems, 2009

A Relational Approach to Novelty Detection in Data Streams.
Proceedings of the Seventeenth Italian Symposium on Advanced Database Systems, 2009

Relational Frequent Patterns Mining for Novelty Detection from Data Streams.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

Novelty Detection from Evolving Complex Data Streams with Time Windows.
Proceedings of the Foundations of Intelligent Systems, 18th International Symposium, 2009

A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams.
Proceedings of the Discovery Science, 12th International Conference, 2009

An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting.
Proceedings of the Discovery Science, 12th International Conference, 2009

Approximate Frequent Itemset Discovery from Data Stream.
Proceedings of the AI*IA 2009: Emergent Perspectives in Artificial Intelligence, 2009

2008
Distributed Discovery of Multi-Level Approximate Process Patterns.
Proceedings of the Sixteenth Italian Symposium on Advanced Database Systems, 2008

Relational Classification based on Emerging Patterns.
Proceedings of the Sixteenth Italian Symposium on Advanced Database Systems, 2008

Discovering Emerging Patterns for Anomaly Detection in Network Connection Data.
Proceedings of the Foundations of Intelligent Systems, 17th International Symposium, 2008

Stepwise Induction of Logistic Model Trees.
Proceedings of the Foundations of Intelligent Systems, 17th International Symposium, 2008

Top-Down Induction of Relational Model Trees in Multi-instance Learning.
Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

Geographic Knowledge Discovery in INGENS: An Inductive Database Perspective.
Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

A Grid-Based Multi-relational Approach to Process Mining.
Proceedings of the Database and Expert Systems Applications, 19th International Conference, 2008

Emerging Pattern Based Classification in Relational Data Mining.
Proceedings of the Database and Expert Systems Applications, 19th International Conference, 2008

2007
On Homogeneity Evaluation and Seed Selection in Clustering Relational Data.
Proceedings of the Fifteenth Italian Symposium on Advanced Database Systems, 2007

Inducing Multi-Target Model Trees in a Stepwise Fashion.
Proceedings of the Fifteenth Italian Symposium on Advanced Database Systems, 2007

Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Transductive Learning from Relational Data.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2007

An Integrated Platform for Spatial Data Mining within a GIS Environment.
Proceedings of the 23rd International Conference on Data Engineering Workshops, 2007

Stepwise Induction of Multi-target Model Trees.
Proceedings of the Machine Learning: ECML 2007, 2007

Discovering Relational Emerging Patterns.
Proceedings of the AI*IA 2007: Artificial Intelligence and Human-Oriented Computing, 2007

2006
Spatial associative classification: propositional vs structural approach.
J. Intell. Inf. Syst., 2006

Classification of symbolic objects: A lazy learning approach.
Intell. Data Anal., 2006

Classifying Aggregated Data: a Symbolic Data Analysis Approach.
Proceedings of the Fourteenth Italian Symposium on Advanced Database Systems, 2006

Supporting Visual Exploration of Discovered Association Rules Through Multi-Dimensional Scaling.
Proceedings of the Foundations of Intelligent Systems, 16th International Symposium, 2006

Mining Tolerance Regions with Model Trees.
Proceedings of the Foundations of Intelligent Systems, 16th International Symposium, 2006

2005
Learning relational model trees.
PhD thesis, 2005

Relational Clustering with Discrete Spatial Structure.
Proceedings of the Thirteenth Italian Symposium on Advanced Database Systems, 2005

Propositionalization Through Relational Association Rules Mining.
Proceedings of the Thirteenth Italian Symposium on Advanced Database Systems, 2005

Mining Model Trees from Spatial Data.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Mining and Filtering Multi-level Spatial Association Rules with ARES.
Proceedings of the Foundations of Intelligent Systems, 15th International Symposium, 2005

Spatial Clustering of Structured Objects.
Proceedings of the Inductive Logic Programming, 15th International Conference, 2005

Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization.
Proceedings of the Innovations in Applied Artificial Intelligence, 2005

Mining Relational Association Rules for Propositional Classification.
Proceedings of the AI*IA 2005: Advances in Artificial Intelligence, 2005

2004
Top-Down Induction of Model Trees with Regression and Splitting Nodes.
IEEE Trans. Pattern Anal. Mach. Intell., 2004

Mining interesting spatial association rules: two case studies.
Proceedings of the Twelfth Italian Symposium on Advanced Database Systems, 2004

Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach.
Proceedings of the Knowledge Discovery in Databases: PKDD 2004, 2004

Redundant feature elimination for multi-class problems.
Proceedings of the Machine Learning, 2004

A Data Mining Query Language for Knowledge Discovery in a Geographical Information System.
Proceedings of the Database Support for Data Mining Applications: Discovering Knowledge with Inductive Queries, 2004

2003
Empowering a GIS with inductive learning capabilities: the case of INGENS.
Comput. Environ. Urban Syst., 2003

Discovery of spatial association rules in geo-referenced census data: A relational mining approach.
Intell. Data Anal., 2003

Stepwise Model Tree Induction in a Multi-Relational Framework.
Proceedings of the Eleventh Italian Symposium on Advanced Database Systems, 2003

Mining Model Trees with Regression and Splitting Nodes.
Proceedings of the Eleventh Italian Symposium on Advanced Database Systems, 2003

Mr-SBC: A Multi-relational Naïve Bayes Classifier.
Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

Simplification Methods for Model Trees with Regression and Splitting Nodes.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2003

MR-SMOTI: A Data Mining System for Regression Tasks Tightly-Coupled with a Relational Database.
Proceedings of the Second International Workshop on Inductive Databases, 2003

Comparing Simplification Methods for Model Trees with Regression and Splitting Nodes.
Proceedings of the Foundations of Intelligent Systems, 14th International Symposium, 2003

Mining Model Trees: A Multi-relational Approach.
Proceedings of the Inductive Logic Programming: 13th International Conference, 2003

Multi-relational Structural Bayesian Classifier.
Proceedings of the AI*IA 2003: Advances in Artificial Intelligence, 2003

2002
Mining Classification and Association Rules in Geographical Data with SDMOQL.
Proceedings of the Decimo Convegno Nazionale su Sistemi Evoluti per Basi di Dati, 2002

KDB2000: Uno strumento per la scoperta della conoscenza.
Proceedings of the Decimo Convegno Nazionale su Sistemi Evoluti per Basi di Dati, 2002

Trading-Off Local versus Global Effects of Regression Nodes in Model Trees.
Proceedings of the Foundations of Intelligent Systems, 13th International Symposium, 2002

2001
Generating Logic Descriptions for the Automated Interpretation of Topographic Maps.
Proceedings of the Graphics Recognition Algorithms and Applications, 2001

Stepwise Induction of Model Trees.
Proceedings of the AI*IA 2001: Advances in Artificial Intelligence, 2001


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