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Annalisa Appice
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- affiliation: University of Bari Aldo Moro, Italy
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2020 – today
- 2024
- [j51]Luca De Rose, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
VINCENT: Cyber-threat detection through vision transformers and knowledge distillation. Comput. Secur. 144: 103926 (2024) - [j50]Muhammad Imran, Annalisa Appice, Donato Malerba:
Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection. Future Internet 16(5): 168 (2024) - [j49]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): 705-733 (2024) - [j48]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
PANACEA: a neural model ensemble for cyber-threat detection. Mach. Learn. 113(8): 5379-5422 (2024) - [j47]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
A Deep Semantic Segmentation Approach to Map Forest Tree Dieback in Sentinel-2 Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 17075-17086 (2024) - [c122]Vincenzo Pasquadibisceglie, Annalisa Appice, Donato Malerba:
LUPIN: A LLM Approach for Activity Suffix Prediction in Business Process Event Logs. ICPM 2024: 1-8 - [c121]Giuseppina Andresini, Annalisa Appice, Dino Ienco, Donato Malerba, Vito Recchia:
Potential of Spectral-Spatial Analysis to Map Forest Tree Dieback Due to Bark Beetle Hotspots in Sentinel-2 Images. IGARSS 2024: 5227-5230 - [c120]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Enhancing Cyber-threat detection coupling Deep Neural Ensemble Learning with XAI. Ital-IA 2024: 182-187 - [c119]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Leveraging Sentinel-2 time series for bark beetle-induced forest dieback inventory. SAC 2024: 875-882 - [c118]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Enhancing Next Activity Prediction with Adversarial Training of Vision Transformers. SEBD 2024: 349-358 - [e14]Annalisa Appice, Hanane Azzag, Mohand-Said Hacid, Allel Hadjali, Zbigniew W. Ras:
Foundations of Intelligent Systems - 27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024, Proceedings. Lecture Notes in Computer Science 14670, Springer 2024, ISBN 978-3-031-62699-9 [contents] - 2023
- [j46]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): 106461 (2023) - [j45]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: 119123 (2023) - [j44]Giuseppina Andresini, Annalisa Appice:
Editorial: AI meets cybersecurity. J. Intell. Inf. Syst. 60(2): 277-279 (2023) - [j43]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): 541-568 (2023) - [j42]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: 10050-10066 (2023) - [j41]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): 2970-2984 (2023) - [c117]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: 205-217 - [c116]Giuseppina Andresini, Annalisa Appice, Roberto Gasbarro, Donato Malerba:
GLORIA: A Graph Convolutional Network-Based Approach for Review Spam Detection. DS 2023: 111-125 - [c115]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
PANACEA: A Neural Model Ensemble for Cyber-Threat Detection. DSAA 2023: 1-2 - [e13]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e12]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - 2022
- [j40]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: 117144 (2022) - [j39]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Wil M. P. van der Aalst:
PROMISE: Coupling predictive process mining to process discovery. Inf. Sci. 606: 250-271 (2022) - [j38]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): 433-452 (2022) - [j37]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): 2382-2395 (2022) - [c114]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
An XAI-based adversarial training approach for cyber-threat detection. DASC/PiCom/CBDCom/CyberSciTech 2022: 1-8 - [c113]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
XAI to Explore Robustness of Features in Adversarial Training for Cybersecurity. ISMIS 2022: 117-126 - [c112]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: 87-98 - [c111]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
A multi-view deep learning approach for predictive business processes monitoring. SERVICES 2022: 26 - 2021
- [j36]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): 2540-2541 (2021) - [j35]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: 108-127 (2021) - [j34]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Autoencoder-based deep metric learning for network intrusion detection. Inf. Sci. 569: 706-727 (2021) - [j33]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): 423-446 (2021) - [j32]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Nearest cluster-based intrusion detection through convolutional neural networks. Knowl. Based Syst. 216: 106798 (2021) - [j31]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): 2991-2992 (2021) - [c110]Giuseppina Andresini, Annalisa Appice, Domenico Dell'Olio, Donato Malerba:
Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images. AI*IA 2021: 478-489 - [c109]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Leveraging Multi-view Deep Learning for Next Activity Prediction. ITBPM@BPM 2021: 1-6 - [c108]Giuseppina Andresini, Feargus Pendlebury, Fabio Pierazzi, Corrado Loglisci, Annalisa Appice, Lorenzo Cavallaro:
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection. AISec@CCS 2021: 111-122 - [c107]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: 111-121 - [c106]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: 385-400 - [c105]Annalisa Appice:
AI meets Cybersecurity. FMEC 2021: 1 - [c104]Vincenzo Pasquadibisceglie, Giovanna Castellano, Annalisa Appice, Donato Malerba:
FOX: a neuro-Fuzzy model for process Outcome prediction and eXplanation. ICPM 2021: 112-119 - [c103]Malik Al-Essa, Annalisa Appice:
Dealing with Imbalanced Data in Multi-class Network Intrusion Detection Systems Using XGBoost. PKDD/ECML Workshops (2) 2021: 5-21 - [c102]Annalisa Appice:
Keynote 4. SDS 2021: 1 - [c101]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
A Two-Step Network Intrusion Detection System for Multi-Class Classification (Discussion Paper). SEBD 2021: 259-266 - 2020
- [j30]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: 52713-52725 (2020) - [j29]Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba:
Multi-Channel Deep Feature Learning for Intrusion Detection. IEEE Access 8: 53346-53359 (2020) - [j28]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: 184073-184086 (2020) - [j27]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): 3179-3200 (2020) - [j26]Annalisa Appice, Giuseppina Andresini, Donato Malerba:
Clustering-Aided Multi-View Classification: A Case Study on Android Malware Detection. J. Intell. Inf. Syst. 55(1): 1-26 (2020) - [c100]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Predictive Process Mining Meets Computer Vision. BPM (Forum) 2020: 176-192 - [c99]Annalisa Appice, Pasquale Ardimento, Donato Malerba, Giuseppe Modugno, Diego Marra, Marco Mottola:
Training in a Virtual Learning Environment: A Process Mining Approach. EAIS 2020: 1-8 - [c98]Antonella Falini, Graziano Castellano, Cristiano Tamborrino, Francesca Mazzia, Rosa Maria Mininni, Annalisa Appice, Donato Malerba:
Saliency Detection for Hyperspectral Images via Sparse-Non Negative-Matrix-Factorization and novel Distance Measures*. EAIS 2020: 1-8 - [c97]Annalisa Appice, Francesco Lomuscio, Antonella Falini, Cristiano Tamborrino, Francesca Mazzia, Donato Malerba:
Saliency Detection in Hyperspectral Images Using Autoencoder-Based Data Reconstruction. ISMIS 2020: 161-170 - [c96]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: 113-124 - [c95]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: 32-39 - [p4]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Dealing with Class Imbalance in Android Malware Detection by Cascading Clustering and Classification. Complex Pattern Mining 2020: 173-187 - [e11]Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin:
Discovery Science - 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings. Lecture Notes in Computer Science 12323, Springer 2020, ISBN 978-3-030-61526-0 [contents] - [e10]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [e9]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras:
Complex Pattern Mining - New Challenges, Methods and Applications. Studies in Computational Intelligence 880, Springer 2020, ISBN 978-3-030-36616-2 [contents]
2010 – 2019
- 2019
- [c94]Annalisa Appice, Nicola Di Mauro, Donato Malerba:
Leveraging Shallow Machine Learning to Predict Business Process Behavior. SCC 2019: 184-188 - [c93]Nicola Di Mauro, Annalisa Appice, Teresa M. A. Basile:
Activity Prediction of Business Process Instances with Inception CNN Models. AI*IA 2019: 348-361 - [c92]Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba:
Exploiting the Auto-Encoder Residual Error for Intrusion Detection. EuroS&P Workshops 2019: 281-290 - [c91]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Using Convolutional Neural Networks for Predictive Process Analytics. ICPM 2019: 129-136 - [c90]Annalisa Appice, Nicola Di Mauro, Francesco Lomuscio, Donato Malerba:
Empowering Change Vector Analysis with Autoencoding in Bi-temporal Hyperspectral Images. MACLEAN@PKDD/ECML 2019 - 2018
- [j25]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): 191-212 (2018) - [j24]Annalisa Appice, Corrado Loglisci, Donato Malerba:
Active learning via collective inference in network regression problems. Inf. Sci. 460-461: 293-317 (2018) - [j23]Annalisa Appice:
Towards mining the organizational structure of a dynamic event scenario. J. Intell. Inf. Syst. 50(1): 165-193 (2018) - [c89]Annalisa Appice, Antonietta Lanza, Donato Malerba:
Handling Multi-scale Data via Multi-target Learning for Wind Speed Forecasting. ISMIS 2018: 357-366 - [c88]Annalisa Appice, Antonietta Lanza, Donato Malerba:
Wind Speed Forecasting via Structured Output Learning. SEBD 2018 - [p3]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Relational Data Mining in the Era of Big Data. A Comprehensive Guide Through the Italian Database Research 2018: 323-339 - [e8]Annalisa Appice, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras:
New Frontiers in Mining Complex Patterns - 6th International Workshop, NFMCP 2017, Held in Conjunction with ECML-PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Revised Selected Papers. Lecture Notes in Computer Science 10785, Springer 2018, ISBN 978-3-319-78679-7 [contents] - 2017
- [j22]Sonja Pravilovic, Massimo Bilancia, Annalisa Appice, Donato Malerba:
Using multiple time series analysis for geosensor data forecasting. Inf. Sci. 380: 31-52 (2017) - [j21]Annalisa Appice, Pietro Guccione, Donato Malerba:
A novel spectral-spatial co-training algorithm for the transductive classification of hyperspectral imagery data. Pattern Recognit. 63: 229-245 (2017) - [c87]Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza:
Sampling Training Data for Accurate Hyperspectral Image Classification via Tree-Based Spatial Clustering. AI*IA 2017: 309-320 - [e7]Marzena Kryszkiewicz, Annalisa Appice, Dominik Slezak, Henryk Rybinski, Andrzej Skowron, Zbigniew W. Ras:
Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Warsaw, Poland, June 26-29, 2017, Proceedings. Lecture Notes in Computer Science 10352, Springer 2017, ISBN 978-3-319-60437-4 [contents] - [e6]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Elio Masciari, Zbigniew W. Ras:
New Frontiers in Mining Complex Patterns - 5th International Workshop, NFMCP 2016, Held in Conjunction with ECML-PKDD 2016, Riva del Garda, Italy, September 19, 2016, Revised Selected Papers. Lecture Notes in Computer Science 10312, Springer 2017, ISBN 978-3-319-61460-1 [contents] - 2016
- [j20]Corrado Loglisci, Annalisa Appice, Donato Malerba:
Collective regression for handling autocorrelation of network data in a transductive setting. J. Intell. Inf. Syst. 46(3): 447-472 (2016) - [j19]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari:
Recent advances in mining patterns from complex data. J. Intell. Inf. Syst. 47(1): 1-3 (2016) - [j18]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): 343-375 (2016) - [j17]Annalisa Appice, Donato Malerba:
A Co-Training Strategy for Multiple View Clustering in Process Mining. IEEE Trans. Serv. Comput. 9(6): 832-845 (2016) - [c86]Annalisa Appice, Pietro Guccione:
Exploiting Spatial Correlation of Spectral Signature for Training Data Selection in Hyperspectral Image Classification. DS 2016: 295-309 - [c85]Anna Maria Crespino, Angelo Corallo, Mariangela Lazoi, Donato Barbagallo, Annalisa Appice, Donato Malerba:
Anomaly detection in aerospace product manufacturing: Initial remarks. RTSI 2016: 1-4 - 2015
- [j16]Annalisa Appice, Anna Ciampi, Donato Malerba:
Summarizing numeric spatial data streams by trend cluster discovery. Data Min. Knowl. Discov. 29(1): 84-136 (2015) - [j15]Pietro Guccione, Luigi Mascolo, Annalisa Appice:
Iterative Hyperspectral Image Classification Using Spectral-Spatial Relational Features. IEEE Trans. Geosci. Remote. Sens. 53(7): 3615-3627 (2015) - [c84]Annalisa Appice, Sonja Pravilovic, Antonietta Lanza, Donato Malerba:
Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning. Discovery Science 2015: 9-16 - [c83]Annalisa Appice, Marco Di Pietro, Claudio Greco, Donato Malerba:
Discovering and Tracking Organizational Structures in Event Logs. NFMCP 2015: 46-60 - [e5]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras:
New Frontiers in Mining Complex Patterns - Third International Workshop, NFMCP 2014, Held in Conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers. Lecture Notes in Computer Science 8983, Springer 2015, ISBN 978-3-319-17875-2 [contents] - [e4]Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, Carlos Soares, João Gama, Alípio Jorge:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I. Lecture Notes in Computer Science 9284, Springer 2015, ISBN 978-3-319-23527-1 [contents] - [e3]Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, João Gama, Alípio Jorge, Carlos Soares:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II. Lecture Notes in Computer Science 9285, Springer 2015, ISBN 978-3-319-23524-0 [contents] - 2014
- [b2]Annalisa Appice, Anna Ciampi, Fabio Fumarola, Donato Malerba:
Data Mining Techniques in Sensor Networks - Summarization, Interpolation and Surveillance. Springer Briefs in Computer Science, Springer 2014, ISBN 978-1-4471-5453-2, pp. I-XIII, 1-105 - [j14]Annalisa Appice, Donato Malerba:
Leveraging the power of local spatial autocorrelation in geophysical interpolative clustering. Data Min. Knowl. Discov. 28(5-6): 1266-1313 (2014) - [j13]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Multi-Relational Model Tree Induction Tightly-Coupled with a Relational Database. Fundam. Informaticae 129(3): 193-224 (2014) - [j12]Annalisa Appice, Pietro Guccione, Donato Malerba, Anna Ciampi:
Dealing with temporal and spatial correlations to classify outliers in geophysical data streams. Inf. Sci. 285: 162-180 (2014) - [j11]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Elio Masciari, Giuseppe Manco:
Mining complex patterns. J. Intell. Inf. Syst. 42(2): 179-180 (2014) - [c82]Sonja Pravilovic, Annalisa Appice, Antonietta Lanza, Donato Malerba:
Wind Power Forecasting Using Time Series Cluster Analysis. Discovery Science 2014: 276-287 - [c81]Sonja Pravilovic, Annalisa Appice, Donato Malerba:
Integrating Cluster Analysis to the ARIMA Model for Forecasting Geosensor Data. ISMIS 2014: 234-243 - [c80]Fabio Fumarola, Annalisa Appice, Donato Malerba:
A Business Intelligence Solution for Monitoring Efficiency of Photovoltaic Power Plants. ISMIS 2014: 518-523 - [c79]Corrado Loglisci, Annalisa Appice, Donato Malerba:
Collective Inference for Handling Autocorrelation in Network Regression. ISMIS 2014: 542-547 - [c78]Sonja Pravilovic, Annalisa Appice, Antonietta Lanza, Donato Malerba:
Mining Cluster-Based Models of Time Series for Wind Power Prediction. SEBD 2014: 9-20 - [c77]Corrado Loglisci, Annalisa Appice, Antonella Montinari, Donato Malerba:
Network Regression in Collective Inference Setting. SEBD 2014: 224-235 - [e2]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras:
New Frontiers in Mining Complex Patterns - Second International Workshop, NFMCP 2013, Held in Conjunction with ECML-PKDD 2013, Prague, Czech Republic, September 27, 2013, Revised Selected Papers. Lecture Notes in Computer Science 8399, Springer 2014, ISBN 978-3-319-08406-0 [contents] - 2013
- [j10]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Dealing with spatial autocorrelation when learning predictive clustering trees. Ecol. Informatics 13: 22-39 (2013) - [j9]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): 119-153 (2013) - [c76]Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza:
Enhancing Regression Models with Spatio-temporal Indicator Additions. AI*IA 2013: 433-444 - [c75]Sonja Pravilovic, Annalisa Appice, Donato Malerba:
An Intelligent Technique for Forecasting Spatially Correlated Time Series. AI*IA 2013: 457-468 - [c74]Annalisa Appice, Sonja Pravilovic, Donato Malerba:
Predictive Regional Trees to Supplement Geo-Physical Random Fields. CORES 2013: 259-268 - [c73]Sonja Pravilovic, Annalisa Appice, Donato Malerba:
Process Mining to Forecast the Future of Running Cases. NFMCP 2013: 67-81 - [e1]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras:
New Frontiers in Mining Complex Patterns - First International Workshop, NFMCP 2012, Held in Conjunction with ECML/PKDD 2012, Bristol, UK, September 24, 2012, Revised Selected Papers. Lecture Notes in Computer Science 7765, Springer 2013, ISBN 978-3-642-37381-7 [contents] - 2012
- [j8]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network regression with predictive clustering trees. Data Min. Knowl. Discov. 25(2): 378-413 (2012) - [c72]Annalisa Appice, Donato Malerba, Anna Ciampi:
Continuously Mining Sliding Window Trend Clusters in a Sensor Network. DEXA (2) 2012: 248-255 - [c71]Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric Paquet, Hongyu Guo:
Transductive Relational Classification in the Co-training Paradigm. MLDM 2012: 11-25 - [c70]Annalisa Appice, Donato Malerba, Antonietta Lanza:
Using Geographic Cost Functions to Discover Vessel Itineraries from AIS Messages. MSM/MUSE 2012: 44-62 - [c69]Pietro Guccione, Anna Ciampi, Annalisa Appice, Donato Malerba, Angelo Muolo:
Trend cluster based interpolation everywhere in a sensor network. SAC 2012: 827-828 - [c68]Anna Ciampi, Annalisa Appice, Pietro Guccione, Donato Malerba:
Integrating Trend Clusters for Spatio-temporal Interpolation of Missing Sensor Data. W2GIS 2012: 203-220 - 2011
- [j7]Annalisa Appice, Michelangelo Ceci, Antonio Turi, Donato Malerba:
A parallel, distributed algorithm for relational frequent pattern discovery from very large data sets. Intell. Data Anal. 15(1): 69-88 (2011) - [c67]Anna Ciampi, Annalisa Appice, Donato Malerba, Pietro Guccione:
Trend cluster based compression of geographically distributed data streams. CIDM 2011: 168-175 - [c66]Corrado Loglisci, Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Discovering process models through relational disjunctive patterns mining. CIDM 2011: 200-207 - [c65]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Global and Local Spatial Autocorrelation in Predictive Clustering Trees. Discovery Science 2011: 307-322 - [c64]Corrado Loglisci, Annalisa Appice, Michelangelo Ceci, Donato Malerba, Floriana Esposito:
MBlab: Molecular Biodiversity Laboratory. IRCDL 2011: 132-135 - [c63]Donato Malerba, Michelangelo Ceci, Annalisa Appice:
Relational Mining in Spatial Domains: Accomplishments and Challenges. ISMIS 2011: 16-24 - [c62]Anna Ciampi, Annalisa Appice, Donato Malerba, Angelo Muolo:
Space-Time Roll-up and Drill-down into Geo-Trend Stream Cubes. ISMIS 2011: 365-375 - [c61]Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network Regression with Predictive Clustering Trees. ECML/PKDD (3) 2011: 333-348 - [c60]Corrado Loglisci, Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Relational Disjunctive Patterns Mining for Discovering Frequent Variants in Process Models. SEBD 2011: 227-238 - [c59]Annalisa Appice, Michelangelo Ceci, Donato Malerba, Antonietta Lanza:
Learning and Transferring Geographically Weighted Regression Trees across Time. MSM/MUSE 2011: 97-117 - [c58]Pietro Guccione, Annalisa Appice, Anna Ciampi, Donato Malerba:
Trend Cluster Based Kriging Interpolation in Sensor Data Networks. MSM/MUSE 2011: 118-137 - 2010
- [c57]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci:
Discovering Informative Syntactic Relationships between Named Entities in Biomedical Literature. DBKDA 2010: 120-125 - [c56]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Time-Slice Density Estimation for Semantic-Based Tourist Destination Suggestion. ECAI 2010: 1107-1108 - [c55]Anna Ciampi, Annalisa Appice, Donato Malerba:
Online and Offline Trend Cluster Discovery in Spatially Distributed Data Streams. MSM/MUSE 2010: 142-161 - [c54]Anna Ciampi, Annalisa Appice, Donato Malerba:
Summarization for Geographically Distributed Data Streams. KES (3) 2010: 339-348 - [c53]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Transductive learning for spatial regression with co-training. SAC 2010: 1065-1070 - [c52]Michelangelo Ceci, Annalisa Appice, Corrado Loglisci, Donato Malerba:
Complex objects ranking: a relational data mining approach. SAC 2010: 1071-1077 - [c51]Michelangelo Ceci, Annalisa Appice, Donato Malerba, Nicola Schirone, Nicola Davide Traversa, Valerio Valrosso:
Suggesting Tourist Destinations by means of Time-Slice Density Estimation. SEBD 2010: 94-105 - [c50]Anna Ciampi, Annalisa Appice, Donato Malerba, Giuseppe Saponaro, Domenico Triglione:
Clustering Spatio-Temporal Data Streams. SEBD 2010: 230-241 - [p2]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Transductive Learning for Spatial Data Classification. Advances in Machine Learning I 2010: 189-207
2000 – 2009
- 2009
- [j6]Donato Malerba, Michelangelo Ceci, Annalisa Appice:
A relational approach to probabilistic classification in a transductive setting. Eng. Appl. Artif. Intell. 22(1): 109-116 (2009) - [c49]Anna Ciampi, Fabio Fumarola, Annalisa Appice, Donato Malerba:
Approximate Frequent Itemset Discovery from Data Stream. AI*IA 2009: 151-160 - [c48]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting. Discovery Science 2009: 36-50 - [c47]Fabio Fumarola, Anna Ciampi, Annalisa Appice, Donato Malerba:
A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams. Discovery Science 2009: 385-392 - [c46]Michelangelo Ceci, Annalisa Appice, Corrado Loglisci, Costantina Caruso, Fabio Fumarola, Donato Malerba:
Novelty Detection from Evolving Complex Data Streams with Time Windows. ISMIS 2009: 563-572 - [c45]Michelangelo Ceci, Annalisa Appice, Corrado Loglisci, Costantina Caruso, Fabio Fumarola, Carmine Valente, Donato Malerba:
Relational Frequent Patterns Mining for Novelty Detection from Data Streams. MLDM 2009: 427-439 - [c44]Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Costantina Caruso, Fabio Fumarola, Michele Todaro, Donato Malerba:
A Relational Approach to Novelty Detection in Data Streams. SEBD 2009: 89-100 - [c43]Annalisa Appice, Michelangelo Ceci, Vincenzo Rizzi, Marco Romano, Donato Malerba:
Spatial Regression in the Transductive Setting. SEBD 2009: 297-304 - [c42]Michelangelo Ceci, Annalisa Appice, Giuseppe De Giosa, Gianluigi Dileo, Alessandro Lallo, Donato Malerba:
Mining preference relations to rank complex object. SEBD 2009: 313-324 - 2008
- [c41]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Emerging Pattern Based Classification in Relational Data Mining. DEXA 2008: 283-296 - [c40]Antonio Turi, Annalisa Appice, Michelangelo Ceci, Donato Malerba:
A Grid-Based Multi-relational Approach to Process Mining. DEXA 2008: 701-709 - [c39]Annalisa Appice, Anna Ciampi, Antonietta Lanza, Donato Malerba, Antonella Rapolla, Luisa Vetturi:
Geographic Knowledge Discovery in INGENS: An Inductive Database Perspective. ICDM Workshops 2008: 326-331 - [c38]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Top-Down Induction of Relational Model Trees in Multi-instance Learning. ILP 2008: 24-41 - [c37]Annalisa Appice, Michelangelo Ceci, Donato Malerba, Savino Saponara:
Stepwise Induction of Logistic Model Trees. ISMIS 2008: 68-77 - [c36]Michelangelo Ceci, Annalisa Appice, Costantina Caruso, Donato Malerba:
Discovering Emerging Patterns for Anomaly Detection in Network Connection Data. ISMIS 2008: 179-188 - [c35]Michelangelo Ceci, Annalisa Appice, Lucrezia Macchia, Donato Malerba:
Relational Classification based on Emerging Patterns. SEBD 2008: 45-56 - [c34]Antonio Turi, Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Distributed Discovery of Multi-Level Approximate Process Patterns. SEBD 2008: 57-68 - 2007
- [c33]Annalisa Appice, Michelangelo Ceci, Carlo Malgieri, Donato Malerba:
Discovering Relational Emerging Patterns. AI*IA 2007: 206-217 - [c32]Annalisa Appice, Saso Dzeroski:
Stepwise Induction of Multi-target Model Trees. ECML 2007: 502-509 - [c31]Annalisa Appice, Antonietta Lanza, Donato Malerba:
An Integrated Platform for Spatial Data Mining within a GIS Environment. ICDE Workshops 2007: 507-516 - [c30]Michelangelo Ceci, Annalisa Appice, Nicola Barile, Donato Malerba:
Transductive Learning from Relational Data. MLDM 2007: 324-338 - [c29]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach. PKDD 2007: 390-397 - [c28]Annalisa Appice, Saso Dzeroski:
Inducing Multi-Target Model Trees in a Stepwise Fashion. SEBD 2007: 16-27 - [c27]Antonio Varlaro, Annalisa Appice, Antonietta Lanza, Antonio Fittipaldi:
On Homogeneity Evaluation and Seed Selection in Clustering Relational Data. SEBD 2007: 471-478 - 2006
- [j5]Annalisa Appice, Claudia d'Amato, Floriana Esposito, Donato Malerba:
Classification of symbolic objects: A lazy learning approach. Intell. Data Anal. 10(4): 301-324 (2006) - [j4]Michelangelo Ceci, Annalisa Appice:
Spatial associative classification: propositional vs structural approach. J. Intell. Inf. Syst. 27(3): 191-213 (2006) - [c26]Margherita Berardi, Annalisa Appice, Corrado Loglisci, Pietro Leo:
Supporting Visual Exploration of Discovered Association Rules Through Multi-Dimensional Scaling. ISMIS 2006: 369-378 - [c25]Annalisa Appice, Michelangelo Ceci:
Mining Tolerance Regions with Model Trees. ISMIS 2006: 560-569 - [c24]Annalisa Appice, Floriana Esposito, Donato Malerba:
Classifying Aggregated Data: a Symbolic Data Analysis Approach. SEBD 2006: 105-116 - 2005
- [b1]Annalisa Appice:
Learning relational model trees. University of Bari, Italy, 2005 - [c23]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Mining Relational Association Rules for Propositional Classification. AI*IA 2005: 522-534 - [c22]Annalisa Appice, Paolo Buono:
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization. IEA/AIE 2005: 448-458 - [c21]Donato Malerba, Annalisa Appice, Antonio Varlaro, Antonietta Lanza:
Spatial Clustering of Structured Objects. ILP 2005: 227-245 - [c20]Annalisa Appice, Margherita Berardi, Michelangelo Ceci, Donato Malerba:
Mining and Filtering Multi-level Spatial Association Rules with ARES. ISMIS 2005: 342-353 - [c19]Donato Malerba, Michelangelo Ceci, Annalisa Appice:
Mining Model Trees from Spatial Data. PKDD 2005: 169-180 - [c18]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Propositionalization Through Relational Association Rules Mining. SEBD 2005: 125-136 - [c17]Antonio Varlaro, Annalisa Appice, Antonietta Lanza, Donato Malerba, Giuseppe Guarnieri:
Relational Clustering with Discrete Spatial Structure. SEBD 2005: 149-160 - 2004
- [j3]Donato Malerba, Floriana Esposito, Michelangelo Ceci, Annalisa Appice:
Top-Down Induction of Model Trees with Regression and Splitting Nodes. IEEE Trans. Pattern Anal. Mach. Intell. 26(5): 612-625 (2004) - [c16]Annalisa Appice, Michelangelo Ceci, Simon Alan Rawles, Peter A. Flach:
Redundant feature elimination for multi-class problems. ICML 2004 - [c15]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach. PKDD 2004: 99-111 - [c14]Annalisa Appice, Margherita Berardi, Michelangelo Ceci, Michele Lapi, Donato Malerba, Antonio Turi:
Mining interesting spatial association rules: two case studies. SEBD 2004: 86-97 - [p1]Donato Malerba, Annalisa Appice, Michelangelo Ceci:
A Data Mining Query Language for Knowledge Discovery in a Geographical Information System. Database Support for Data Mining Applications 2004: 95-116 - 2003
- [j2]Annalisa Appice, Michelangelo Ceci, Antonietta Lanza, Francesca A. Lisi, Donato Malerba:
Discovery of spatial association rules in geo-referenced census data: A relational mining approach. Intell. Data Anal. 7(6): 541-566 (2003) - [j1]Donato Malerba, Floriana Esposito, Antonietta Lanza, Francesca A. Lisi, Annalisa Appice:
Empowering a GIS with inductive learning capabilities: the case of INGENS. Comput. Environ. Urban Syst. 27(3): 265-281 (2003) - [c13]Michelangelo Ceci, Annalisa Appice, Donato Malerba, Vincenzo Colonna:
Multi-relational Structural Bayesian Classifier. AI*IA 2003: 250-261 - [c12]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Mining Model Trees: A Multi-relational Approach. ILP 2003: 4-21 - [c11]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Comparing Simplification Methods for Model Trees with Regression and Splitting Nodes. ISMIS 2003: 49-56 - [c10]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
MR-SMOTI: A Data Mining System for Regression Tasks Tightly-Coupled with a Relational Database. KDID 2003: 17-27 - [c9]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Simplification Methods for Model Trees with Regression and Splitting Nodes. MLDM 2003: 20-34 - [c8]Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Mr-SBC: A Multi-relational Naïve Bayes Classifier. PKDD 2003: 95-106 - [c7]Annalisa Appice, Michelangelo Ceci, Donato Malerba, D. Sacchi:
Stepwise Model Tree Induction in a Multi-Relational Framework. SEBD 2003: 281-292 - [c6]Annalisa Appice, Michelangelo Ceci, Floriana Esposito, Donato Malerba:
Mining Model Trees with Regression and Splitting Nodes. SEBD 2003: 495-506 - 2002
- [c5]Donato Malerba, Annalisa Appice, Michelangelo Ceci, Marianna Monopoli:
Trading-Off Local versus Global Effects of Regression Nodes in Model Trees. ISMIS 2002: 393-402 - [c4]Donato Malerba, Annalisa Appice, Michelangelo Ceci, Nicola Vacca:
Mining Classification and Association Rules in Geographical Data with SDMOQL. SEBD 2002: 251-264 - [c3]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
KDB2000: Uno strumento per la scoperta della conoscenza. SEBD 2002: 417-421 - 2001
- [c2]Donato Malerba, Annalisa Appice, Antonia Bellino, Michelangelo Ceci, Domenico Pallotta:
Stepwise Induction of Model Trees. AI*IA 2001: 20-32 - [c1]Antonietta Lanza, Donato Malerba, Francesca A. Lisi, Annalisa Appice, Michelangelo Ceci:
Generating Logic Descriptions for the Automated Interpretation of Topographic Maps. GREC 2001: 200-210
Coauthor Index
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