Annalisa Appice is an Assistant Professor at the Department of Computer Science, University of Bari, Italy. She received a Ph.D. in Computer Science with the thesis “Learning Reltional Model Trees”. She was visiting researcher at the University of Bristol (U.K.) and at the Jozef Stefan Institute (Slovenia). Her current research interests include knowledge discovery and data mining, big data analytics, stream data mining, spatio-temporal data mining, remote sensed data analysis, network data analysis and process mining. She has been Program co-Chair of DS 2020, ECML-PKDD 2015 and ISMIS 2017. She is serving/has served in the program committee of several international/national conferences, including: AAAI, IEEE ICDM, KDD, ICML, IJCAI, ECMLPKDD, CIKM, DEXA, ACM SAC. She is a member of the editorial board of the Journal of Intelligent Information Systems. She has participated in the organization (as co-chair) of six international workshops and one national workshop. She has acted as guest-editor of three special issues of international journals. She is member of the steering committee of ECML PKDD (2016-2018) and ISMIS (2018-2020).

Research Interests

Analysis and synthesis of algorithms for inductive inference: classification and model trees. Clustering, Association Rule Discovery, Associative Classification. Applications include Knowledge Discovery in Databases and Data Mining, (multi)Relational Data Mining, Data Stream Mining, Map Interpretation and Spatial Data Mining, Data Mining Query Language.

Annalisa Appice
PhD, Assistant Professor
Phone: +39 080 5443262
Fax: +39 080 5443269
em@il: annalisa.appice @ uniba.it
webpage: http://www.di.uniba.it/~appice





Publications Legend

Journal Articles
Book
Conference or Workshop
Editorship
Collection
Other

Publications


2020

Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin:
Discovery Science - 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings DS Lecture Notes in Computer Science 12323, Springer (2020), ISBN: 978-3-030-61527-7
DOI: https://doi.org/10.1007/978-3-030-61527-7
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Predictive Process Mining Meets Computer Vision. BPM (Forum): 176-192 (2020)
DOI: https://doi.org/10.1007/978-3-030-58638-6_11
Annalisa Appice, Francesco Lomuscio, Antonella Falini, Cristiano Tamborrino, Francesca Mazzia, Donato Malerba:
Saliency Detection in Hyperspectral Images Using Autoencoder-Based Data Reconstruction. ISMIS: 161-170 (2020)
DOI: https://doi.org/10.1007/978-3-030-59491-6_15
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)
DOI: https://doi.org/10.1007/s10489-020-01701-8
Annalisa Appice, Pasquale Ardimento, Donato Malerba, Giuseppe Modugno, Diego Marra, Marco Mottola:
Training in a Virtual Learning Environment: A Process Mining Approach. EAIS: 1-8 (2020)
DOI: https://doi.org/10.1109/EAIS48028.2020.9122760
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: 1-8 (2020)
DOI: https://doi.org/10.1109/EAIS48028.2020.9122749
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)
DOI: https://doi.org/10.1007/s10844-020-00598-6
Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba:
Multi-Channel Deep Feature Learning for Intrusion Detection. IEEE Access 8: 53346-5335 (2020)
DOI: https://doi.org/10.1109/ACCESS.2020.2980937
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: 52713-5272 (2020)
DOI: https://doi.org/10.1109/ACCESS.2020.2980634
Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras:
Complex Pattern Mining - New Challenges, Methods and Applications Complex Pattern Mining Studies in Computational Intelligence 880, Springer (2020), ISBN: 978-3-030-36617-9
DOI: https://doi.org/10.1007/978-3-030-36617-9
Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Dealing with Class Imbalance in Android Malware Detection by Cascading Clustering and Classification. Complex Pattern Mining: 173-187 (2020)
DOI: https://doi.org/10.1007/978-3-030-36617-9_11


2019

Nicola Di Mauro, Annalisa Appice, Teresa M. A. Basile:
Activity Prediction of Business Process Instances with Inception CNN Models. AI*IA: 348-361 (2019)
DOI: https://doi.org/10.1007/978-3-030-35166-3_25
Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba:
Exploiting the Auto-Encoder Residual Error for Intrusion Detection. EuroS&P Workshops: 281-290 (2019)
DOI: https://doi.org/10.1109/EuroSPW.2019.00038
Annalisa Appice, Nicola Di Mauro, Donato Malerba:
Leveraging Shallow Machine Learning to Predict Business Process Behavior. SCC: 184-188 (2019)
DOI: https://doi.org/10.1109/SCC.2019.00039
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Using Convolutional Neural Networks for Predictive Process Analytics. ICPM: 129-136 (2019)
DOI: https://doi.org/10.1109/ICPM.2019.00028


2018

Annalisa Appice, Antonietta Lanza, Donato Malerba:
Wind Speed Forecasting via Structured Output Learning. SEBD (2018)
DOI: http://ceur-ws.org/Vol-2161/paper31.pdf
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 NFMCP@PKDD/ECML Lecture Notes in Computer Science 10785, Springer (2018), ISBN: 978-3-319-78680-3
DOI: https://doi.org/10.1007/978-3-319-78680-3
Sonja Pravilovic, Annalisa Appice, Donato Malerba:
Leveraging correlation across space and time to interpolate geophysical data via CoKriging. International Journal of Geographical Information Science 32(1): 191-212 (2018)
DOI: https://doi.org/10.1080/13658816.2017.1381338
Annalisa Appice, Antonietta Lanza, Donato Malerba:
Handling Multi-scale Data via Multi-target Learning for Wind Speed Forecasting. ISMIS: 357-366 (2018)
DOI: https://doi.org/10.1007/978-3-030-01851-1_34
Annalisa Appice, Corrado Loglisci, Donato Malerba:
Active learning via collective inference in network regression problems. Inf. Sci. 460: 293-317 (2018)
DOI: https://doi.org/10.1016/j.ins.2018.05.028
Annalisa Appice:
Towards mining the organizational structure of a dynamic event scenario. J. Intell. Inf. Syst. 50(1): 165-193 (2018)
DOI: https://doi.org/10.1007/s10844-017-0451-x
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Relational Data Mining in the Era of Big Data. A Comprehensive Guide Through the Italian Database Research: 323-339 (2018)
DOI: https://doi.org/10.1007/978-3-319-61893-7_19


2017

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 ISMIS Lecture Notes in Computer Science 10352, Springer (2017), ISBN: 978-3-319-60438-1
DOI: https://doi.org/10.1007/978-3-319-60438-1
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 NFMCP@ECML/PKDD Lecture Notes in Computer Science 10312, Springer (2017), ISBN: 978-3-319-61461-8
DOI: https://doi.org/10.1007/978-3-319-61461-8
Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza:
Sampling Training Data for Accurate Hyperspectral Image Classification via Tree-Based Spatial Clustering. AI*IA: 309-320 (2017)
DOI: https://doi.org/10.1007/978-3-319-70169-1_23
Sonja Pravilovic, Massimo Bilancia, Annalisa Appice, Donato Malerba:
Using multiple time series analysis for geosensor data forecasting. Inf. Sci. 380: 31-52 (2017)
DOI: https://doi.org/10.1016/j.ins.2016.11.001
Annalisa Appice, Pietro Guccione, Donato Malerba:
A novel spectral-spatial co-training algorithm for the transductive classification of hyperspectral imagery data. Pattern Recognition 63: 229-245 (2017)
DOI: https://doi.org/10.1016/j.patcog.2016.10.010


2016

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)
DOI: https://doi.org/10.1007/s10844-016-0415-6
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)
DOI: https://doi.org/10.1007/s10844-015-0361-8
Annalisa Appice, Pietro Guccione, Donato Malerba:
Transductive hyperspectral image classification: toward integrating spectral and relational features via an iterative ensemble system. Machine Learning 103(3): 343-375 (2016)
DOI: https://doi.org/10.1007/s10994-016-5559-7
Annalisa Appice, Donato Malerba:
A Co-Training Strategy for Multiple View Clustering in Process Mining. IEEE Trans. Services Computing 9(6): 832-845 (2016)
DOI: https://doi.org/10.1109/TSC.2015.2430327
Annalisa Appice, Pietro Guccione:
Exploiting Spatial Correlation of Spectral Signature for Training Data Selection in Hyperspectral Image Classification. DS: 295-309 (2016)
DOI: https://doi.org/10.1007/978-3-319-46307-0_19
Anna Maria Crespino, Angelo Corallo, Mariangela Lazoi, Donato Barbagallo, Annalisa Appice, Donato Malerba:
Anomaly detection in aerospace product manufacturing: Initial remarks. RTSI: 1-4 (2016)
DOI: https://doi.org/10.1109/RTSI.2016.7740644


2015

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 NFMCP Lecture Notes in Computer Science 8983, Springer (2015), ISBN: 978-3-319-17875-2
DOI: https://doi.org/10.1007/978-3-319-17876-9
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 ECML/PKDD (1) Lecture Notes in Computer Science 9284, Springer (2015), ISBN: 978-3-319-23527-1
DOI: https://doi.org/10.1007/978-3-319-23528-8
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 ECML/PKDD (2) Lecture Notes in Computer Science 9285, Springer (2015), ISBN: 978-3-319-23524-0
DOI: https://doi.org/10.1007/978-3-319-23525-7
Annalisa Appice, Sonja Pravilovic, Antonietta Lanza, Donato Malerba:
Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning. Discovery Science: 9-16 (2015)
DOI: https://doi.org/10.1007/978-3-319-24282-8_2
Annalisa Appice, Marco Di Pietro, Claudio Greco, Donato Malerba:
Discovering and Tracking Organizational Structures in Event Logs. NFMCP: 46-60 (2015)
DOI: https://doi.org/10.1007/978-3-319-39315-5_4
Annalisa Appice, Anna Ciampi, Donato Malerba:
Summarizing numeric spatial data streams by trend cluster discovery. Data Min. Knowl. Discov. 29(1): 84-136 (2015)
DOI: https://doi.org/10.1007/s10618-013-0337-7
Pietro Guccione, Luigi Mascolo, Annalisa Appice:
Iterative Hyperspectral Image Classification Using Spectral-Spatial Relational Features. IEEE Trans. Geoscience and Remote Sensing 53(7): 3615-3627 (2015)
DOI: https://doi.org/10.1109/TGRS.2014.2380475


2014

Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Elio Masciari, Giuseppe Manco:
Mining complex patterns. J. Intell. Inf. Syst. 42(2): 179-180 (2014)
DOI: https://doi.org/10.1007/s10844-013-0301-4
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 NFMCP Lecture Notes in Computer Science 8399, Springer (2014), ISBN: 978-3-319-08406-0
DOI: https://doi.org/10.1007/978-3-319-08407-7
Fabio Fumarola, Annalisa Appice, Donato Malerba:
A Business Intelligence Solution for Monitoring Efficiency of Photovoltaic Power Plants. ISMIS: 518-523 (2014)
DOI: https://doi.org/10.1007/978-3-319-08326-1_54
Corrado Loglisci, Annalisa Appice, Donato Malerba:
Collective Inference for Handling Autocorrelation in Network Regression. ISMIS: 542-547 (2014)
DOI: https://doi.org/10.1007/978-3-319-08326-1_58
Sonja Pravilovic, Annalisa Appice, Donato Malerba:
Integrating Cluster Analysis to the ARIMA Model for Forecasting Geosensor Data. ISMIS: 234-243 (2014)
DOI: https://doi.org/10.1007/978-3-319-08326-1_24
Annalisa Appice, Donato Malerba:
Leveraging the power of local spatial autocorrelation in geophysical interpolative clustering. Data Min. Knowl. Discov. 28(5): 1266-1313 (2014)
DOI: https://doi.org/10.1007/s10618-014-0372-z
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)
DOI: https://doi.org/10.1016/j.ins.2013.12.009
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Multi-Relational Model Tree Induction Tightly-Coupled with a Relational Database. Fundam. Inform. 129(3): 193-224 (2014)
DOI: https://doi.org/10.3233/FI-2014-969
Sonja Pravilovic, Annalisa Appice, Antonietta Lanza, Donato Malerba:
Wind Power Forecasting Using Time Series Cluster Analysis. Discovery Science: 276-287 (2014)
DOI: https://doi.org/10.1007/978-3-319-11812-3_24
Annalisa Appice, Anna Ciampi, Fabio Fumarola, Donato Malerba:
Data Mining Techniques in Sensor Networks - Summarization, Interpolation and Surveillance. Springer Briefs in Computer Science, Springer: I-XIII, 1- (2014), ISBN: 978-1-4471-5453-2
DOI: https://doi.org/10.1007/978-1-4471-5454-9
Corrado Loglisci, Annalisa Appice, Antonella Montinari, Donato Malerba:
Network Regression in Collective Inference Setting. SEBD: 224-235 (2014)
Sonja Pravilovic, Annalisa Appice, Antonietta Lanza, Donato Malerba:
Mining Cluster-Based Models of Time Series for Wind Power Prediction. SEBD: 9-20 (2014)


2013

Annalisa Appice, Anna Ciampi, Donato Malerba, Pietro Guccione:
Using trend clusters for spatiotemporal interpolation of missing data in a sensor network. J. Spatial Information Science 6(1): 119-153 (2013)
DOI: https://doi.org/10.5311/JOSIS.2013.6.102
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 NFMCP Lecture Notes in Computer Science 7765, Springer (2013), ISBN: 978-3-642-37381-7
DOI: https://doi.org/10.1007/978-3-642-37382-4
Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza:
Enhancing Regression Models with Spatio-temporal Indicator Additions. AI*IA: 433-444 (2013)
DOI: https://doi.org/10.1007/978-3-319-03524-6_37
Sonja Pravilovic, Annalisa Appice, Donato Malerba:
An Intelligent Technique for Forecasting Spatially Correlated Time Series. AI*IA: 457-468 (2013)
DOI: https://doi.org/10.1007/978-3-319-03524-6_39
Annalisa Appice, Sonja Pravilovic, Donato Malerba:
Predictive Regional Trees to Supplement Geo-Physical Random Fields. CORES: 259-268 (2013)
DOI: https://doi.org/10.1007/978-3-319-00969-8_25
Sonja Pravilovic, Annalisa Appice, Donato Malerba:
Process Mining to Forecast the Future of Running Cases. NFMCP: 67-81 (2013)
DOI: https://doi.org/10.1007/978-3-319-08407-7_5
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Dealing with spatial autocorrelation when learning predictive clustering trees. Ecological Informatics 13: 22-39 (2013)
DOI: https://doi.org/10.1016/j.ecoinf.2012.10.006


2012

Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network regression with predictive clustering trees. Data Min. Knowl. Discov. 25(2): 378-413 (2012)
DOI: https://doi.org/10.1007/s10618-012-0278-6
Annalisa Appice, Donato Malerba, Anna Ciampi:
Continuously Mining Sliding Window Trend Clusters in a Sensor Network. DEXA (2): 248-255 (2012)
DOI: https://doi.org/10.1007/978-3-642-32597-7_22
Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric Paquet, Hongyu Guo:
Transductive Relational Classification in the Co-training Paradigm. MLDM: 11-25 (2012)
DOI: https://doi.org/10.1007/978-3-642-31537-4_2
Annalisa Appice, Donato Malerba, Antonietta Lanza:
Using Geographic Cost Functions to Discover Vessel Itineraries from AIS Messages. MSM/MUSE: 44-62 (2012)
DOI: https://doi.org/10.1007/978-3-642-45392-2_3
Pietro Guccione, Anna Ciampi, Annalisa Appice, Donato Malerba, Angelo Muolo:
Trend cluster based interpolation everywhere in a sensor network. SAC: 827-828 (2012)
DOI: https://doi.org/10.1145/2245276.2245436
Anna Ciampi, Annalisa Appice, Pietro Guccione, Donato Malerba:
Integrating Trend Clusters for Spatio-temporal Interpolation of Missing Sensor Data. W2GIS: 203-220 (2012)
DOI: https://doi.org/10.1007/978-3-642-29247-7_15


2011

Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Saso Dzeroski:
Network Regression with Predictive Clustering Trees. ECML/PKDD (3): 333-348 (2011)
DOI: https://doi.org/10.1007/978-3-642-23808-6_22
Anna Ciampi, Annalisa Appice, Donato Malerba, Pietro Guccione:
Trend cluster based compression of geographically distributed data streams. CIDM: 168-175 (2011)
DOI: https://doi.org/10.1109/CIDM.2011.5949298
Corrado Loglisci, Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Discovering process models through relational disjunctive patterns mining. CIDM: 200-207 (2011)
DOI: https://doi.org/10.1109/CIDM.2011.5949299
Daniela Stojanova, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Saso Dzeroski:
Global and Local Spatial Autocorrelation in Predictive Clustering Trees. Discovery Science: 307-322 (2011)
DOI: https://doi.org/10.1007/978-3-642-24477-3_25
Corrado Loglisci, Annalisa Appice, Michelangelo Ceci, Donato Malerba, Floriana Esposito:
MBlab: Molecular Biodiversity Laboratory. IRCDL: 132-135 (2011)
DOI: https://doi.org/10.1007/978-3-642-27302-5_18
Anna Ciampi, Annalisa Appice, Donato Malerba, Angelo Muolo:
Space-Time Roll-up and Drill-down into Geo-Trend Stream Cubes. ISMIS: 365-375 (2011)
DOI: https://doi.org/10.1007/978-3-642-21916-0_40
Donato Malerba, Michelangelo Ceci, Annalisa Appice:
Relational Mining in Spatial Domains: Accomplishments and Challenges. ISMIS: 16-24 (2011)
DOI: https://doi.org/10.1007/978-3-642-21916-0_2
Annalisa Appice, Michelangelo Ceci, Donato Malerba, Antonietta Lanza:
Learning and Transferring Geographically Weighted Regression Trees across Time. MSM/MUSE: 97-117 (2011)
DOI: https://doi.org/10.1007/978-3-642-33684-3_6
Pietro Guccione, Annalisa Appice, Anna Ciampi, Donato Malerba:
Trend Cluster Based Kriging Interpolation in Sensor Data Networks. MSM/MUSE: 118-137 (2011)
DOI: https://doi.org/10.1007/978-3-642-33684-3_7
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)
DOI: https://doi.org/10.3233/IDA-2010-0456
Corrado Loglisci, Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Relational Disjunctive Patterns Mining for Discovering Frequent Variants in Process Models. SEBD: 227-238 (2011)


2010

Annalisa Appice, Michelangelo Ceci, Corrado Loglisci:
Discovering Informative Syntactic Relationships between Named Entities in Biomedical Literature. DBKDA: 120-125 (2010)
DOI: https://doi.org/10.1109/DBKDA.2010.14
Anna Ciampi, Annalisa Appice, Donato Malerba:
Online and Offline Trend Cluster Discovery in Spatially Distributed Data Streams. MSM/MUSE: 142-161 (2010)
DOI: https://doi.org/10.1007/978-3-642-23599-3_8
Anna Ciampi, Annalisa Appice, Donato Malerba:
Summarization for Geographically Distributed Data Streams. KES (3): 339-348 (2010)
DOI: https://doi.org/10.1007/978-3-642-15393-8_39
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Transductive learning for spatial regression with co-training. SAC: 1065-1070 (2010)
DOI: https://doi.org/10.1145/1774088.1774310
Michelangelo Ceci, Annalisa Appice, Corrado Loglisci, Donato Malerba:
Complex objects ranking: a relational data mining approach. SAC: 1071-1077 (2010)
DOI: https://doi.org/10.1145/1774088.1774311
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Transductive Learning for Spatial Data Classification. Advances in Machine Learning I: 189-207 (2010)
DOI: https://doi.org/10.1007/978-3-642-05177-7_9
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Time-Slice Density Estimation for Semantic-Based Tourist Destination Suggestion. ECAI: 1107-1108 (2010)
DOI: https://doi.org/10.3233/978-1-60750-606-5-1107
Michelangelo Ceci, Annalisa Appice, Donato Malerba, Nicola Schirone, Nicola Davide Traversa, Valerio Valrosso:
Suggesting Tourist Destinations by means of Time-Slice Density Estimation. SEBD: 94-105 (2010)
Anna Ciampi, Annalisa Appice, Donato Malerba, Giuseppe Saponaro, Domenico Triglione:
Clustering Spatio-Temporal Data Streams. SEBD: 230-241 (2010)


2009

Anna Ciampi, Fabio Fumarola, Annalisa Appice, Donato Malerba:
Approximate Frequent Itemset Discovery from Data Stream. AI*IA: 151-160 (2009)
DOI: https://doi.org/10.1007/978-3-642-10291-2_16
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting. Discovery Science: 36-50 (2009)
DOI: https://doi.org/10.1007/978-3-642-04747-3_6
Fabio Fumarola, Anna Ciampi, Annalisa Appice, Donato Malerba:
A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams. Discovery Science: 385-392 (2009)
DOI: https://doi.org/10.1007/978-3-642-04747-3_30
Michelangelo Ceci, Annalisa Appice, Corrado Loglisci, Costantina Caruso, Fabio Fumarola, Donato Malerba:
Novelty Detection from Evolving Complex Data Streams with Time Windows. ISMIS: 563-572 (2009)
DOI: https://doi.org/10.1007/978-3-642-04125-9_59
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: 427-439 (2009)
DOI: https://doi.org/10.1007/978-3-642-03070-3_32
Donato Malerba, Michelangelo Ceci, Annalisa Appice:
A relational approach to probabilistic classification in a transductive setting. Eng. Appl. of AI 22(1): 109-116 (2009)
DOI: https://doi.org/10.1016/j.engappai.2008.04.005
Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Costantina Caruso, Fabio Fumarola, Michele Todaro, Donato Malerba:
A Relational Approach to Novelty Detection in Data Streams. SEBD: 89-100 (2009)
Annalisa Appice, Michelangelo Ceci, Vincenzo Rizzi, Marco Romano, Donato Malerba:
Spatial Regression in the Transductive Setting. SEBD: 297-304 (2009)
Michelangelo Ceci, Annalisa Appice, Giuseppe De Giosa, Gianluigi Dileo, Alessandro Lallo, Donato Malerba:
Mining preference relations to rank complex object. SEBD: 313-324 (2009)


2008

Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Emerging Pattern Based Classification in Relational Data Mining. DEXA: 283-296 (2008)
DOI: https://doi.org/10.1007/978-3-540-85654-2_28
Antonio Turi, Annalisa Appice, Michelangelo Ceci, Donato Malerba:
A Grid-Based Multi-relational Approach to Process Mining. DEXA: 701-709 (2008)
DOI: https://doi.org/10.1007/978-3-540-85654-2_61
Annalisa Appice, Anna Ciampi, Antonietta Lanza, Donato Malerba, Antonella Rapolla, Luisa Vetturi:
Geographic Knowledge Discovery in INGENS: An Inductive Database Perspective. ICDM Workshops: 326-331 (2008)
DOI: https://doi.org/10.1109/ICDMW.2008.120
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Top-Down Induction of Relational Model Trees in Multi-instance Learning. ILP: 24-41 (2008)
DOI: https://doi.org/10.1007/978-3-540-85928-4_7
Annalisa Appice, Michelangelo Ceci, Donato Malerba, Savino Saponara:
Stepwise Induction of Logistic Model Trees. ISMIS: 68-77 (2008)
DOI: https://doi.org/10.1007/978-3-540-68123-6_7
Michelangelo Ceci, Annalisa Appice, Costantina Caruso, Donato Malerba:
Discovering Emerging Patterns for Anomaly Detection in Network Connection Data. ISMIS: 179-188 (2008)
DOI: https://doi.org/10.1007/978-3-540-68123-6_20
Michelangelo Ceci, Annalisa Appice, Lucrezia Macchia, Donato Malerba:
Relational Classification based on Emerging Patterns. SEBD: 45-56 (2008)
Antonio Turi, Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Distributed Discovery of Multi-Level Approximate Process Patterns. SEBD: 57-68 (2008)


2007

Annalisa Appice, Antonietta Lanza, Donato Malerba:
An Integrated Platform for Spatial Data Mining within a GIS Environment. ICDE Workshops: 507-516 (2007)
DOI: https://doi.org/10.1109/ICDEW.2007.4401036
Annalisa Appice, Saso Dzeroski:
Stepwise Induction of Multi-target Model Trees. ECML: 502-509 (2007)
DOI: https://doi.org/10.1007/978-3-540-74958-5_46
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach. PKDD: 390-397 (2007)
DOI: https://doi.org/10.1007/978-3-540-74976-9_38
Annalisa Appice, Michelangelo Ceci, Carlo Malgieri, Donato Malerba:
Discovering Relational Emerging Patterns. AI*IA: 206-217 (2007)
DOI: https://doi.org/10.1007/978-3-540-74782-6_19
Michelangelo Ceci, Annalisa Appice, Nicola Barile, Donato Malerba:
Transductive Learning from Relational Data. MLDM: 324-338 (2007)
DOI: https://doi.org/10.1007/978-3-540-73499-4_25
Annalisa Appice, Saso Dzeroski:
Inducing Multi-Target Model Trees in a Stepwise Fashion. SEBD: 16-27 (2007)
Antonio Varlaro, Annalisa Appice, Antonietta Lanza, Antonio Fittipaldi:
On Homogeneity Evaluation and Seed Selection in Clustering Relational Data. SEBD: 471-478 (2007)


2006

Michelangelo Ceci, Annalisa Appice:
Spatial associative classification: propositional vs structural approach. J. Intell. Inf. Syst. 27(3): 191-213 (2006)
DOI: https://doi.org/10.1007/s10844-006-9950-x
Annalisa Appice, Michelangelo Ceci:
Mining Tolerance Regions with Model Trees. ISMIS: 560-569 (2006)
DOI: https://doi.org/10.1007/11875604_63
Margherita Berardi, Annalisa Appice, Corrado Loglisci, Pietro Leo:
Supporting Visual Exploration of Discovered Association Rules Through Multi-Dimensional Scaling. ISMIS: 369-378 (2006)
DOI: https://doi.org/10.1007/11875604_43
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)
DOI: http://content.iospress.com/articles/intelligent-data-analysis/ida00252
Annalisa Appice, Floriana Esposito, Donato Malerba:
Classifying Aggregated Data: a Symbolic Data Analysis Approach. SEBD: 105-116 (2006)


2005

Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Mining Relational Association Rules for Propositional Classification. AI*IA: 522-534 (2005)
DOI: https://doi.org/10.1007/11558590_53
Donato Malerba, Michelangelo Ceci, Annalisa Appice:
Mining Model Trees from Spatial Data. PKDD: 169-180 (2005)
DOI: https://doi.org/10.1007/11564126_20
Donato Malerba, Annalisa Appice, Antonio Varlaro, Antonietta Lanza:
Spatial Clustering of Structured Objects. ILP: 227-245 (2005)
DOI: https://doi.org/10.1007/11536314_14
Annalisa Appice, Margherita Berardi, Michelangelo Ceci, Donato Malerba:
Mining and Filtering Multi-level Spatial Association Rules with ARES. ISMIS: 342-353 (2005)
DOI: https://doi.org/10.1007/11425274_36
Annalisa Appice, Paolo Buono:
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization. IEA/AIE: 448-458 (2005)
DOI: https://doi.org/10.1007/11504894_63
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Propositionalization Through Relational Association Rules Mining. SEBD: 125-136 (2005)
Antonio Varlaro, Annalisa Appice, Antonietta Lanza, Donato Malerba, Giuseppe Guarnieri:
Relational Clustering with Discrete Spatial Structure. SEBD: 149-160 (2005)


2004

Annalisa Appice, Michelangelo Ceci, Simon Alan Rawles, Peter A. Flach:
Redundant feature elimination for multi-class problems. ICML (2004)
DOI: https://doi.org/10.1145/1015330.1015397
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)
DOI: https://doi.org/10.1109/TPAMI.2004.1273937
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: 95-116 (2004)
DOI: https://doi.org/10.1007/978-3-540-44497-8_5
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach. PKDD: 99-111 (2004)
DOI: https://doi.org/10.1007/978-3-540-30116-5_12
Annalisa Appice, Margherita Berardi, Michelangelo Ceci, Michele Lapi, Donato Malerba, Antonio Turi:
Mining interesting spatial association rules: two case studies. SEBD: 86-97 (2004)


2003

Donato Malerba, Floriana Esposito, Antonietta Lanza, Francesca A. Lisi, Annalisa Appice:
Empowering a GIS with inductive learning capabilities: the case of INGENS. Computers, Environment and Urban Systems 27(3): 265-281 (2003)
DOI: https://doi.org/10.1016/S0198-9715(02)00024-8
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Comparing Simplification Methods for Model Trees with Regression and Splitting Nodes. ISMIS: 49-56 (2003)
DOI: https://doi.org/10.1007/978-3-540-39592-8_8
Michelangelo Ceci, Annalisa Appice, Donato Malerba, Vincenzo Colonna:
Multi-relational Structural Bayesian Classifier. AI*IA: 250-261 (2003)
DOI: https://doi.org/10.1007/978-3-540-39853-0_21
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Mr-SBC: A Multi-relational Naïve Bayes Classifier. PKDD: 95-106 (2003)
DOI: https://doi.org/10.1007/978-3-540-39804-2_11
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Mining Model Trees: A Multi-relational Approach. ILP: 4-21 (2003)
DOI: https://doi.org/10.1007/978-3-540-39917-9_3
Michelangelo Ceci, Annalisa Appice, Donato Malerba:
Simplification Methods for Model Trees with Regression and Splitting Nodes. MLDM: 20-34 (2003)
DOI: https://doi.org/10.1007/3-540-45065-3_3
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)
DOI: http://content.iospress.com/articles/intelligent-data-analysis/ida00146
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
MR-SMOTI: A Data Mining System for Regression Tasks Tightly-Coupled with a Relational Database. KDID: 17-27 (2003)
Annalisa Appice, Michelangelo Ceci, Floriana Esposito, Donato Malerba:
Mining Model Trees with Regression and Splitting Nodes. SEBD: 495-506 (2003)
Annalisa Appice, Michelangelo Ceci, Donato Malerba, D. Sacchi:
Stepwise Model Tree Induction in a Multi-Relational Framework. SEBD: 281-292 (2003)


2002

Donato Malerba, Annalisa Appice, Michelangelo Ceci, Marianna Monopoli:
Trading-Off Local versus Global Effects of Regression Nodes in Model Trees. ISMIS: 393-402 (2002)
DOI: https://doi.org/10.1007/3-540-48050-1_43
Annalisa Appice, Michelangelo Ceci, Donato Malerba:
KDB2000: Uno strumento per la scoperta della conoscenza. SEBD: 417-421 (2002)
Donato Malerba, Annalisa Appice, Michelangelo Ceci, Nicola Vacca:
Mining Classification and Association Rules in Geographical Data with SDMOQL. SEBD: 251-264 (2002)


2001

Donato Malerba, Annalisa Appice, Antonia Bellino, Michelangelo Ceci, Domenico Pallotta:
Stepwise Induction of Model Trees. AI*IA: 20-32 (2001)
DOI: https://doi.org/10.1007/3-540-45411-X_3
Antonietta Lanza, Donato Malerba, Francesca A. Lisi, Annalisa Appice, Michelangelo Ceci:
Generating Logic Descriptions for the Automated Interpretation of Topographic Maps. GREC: 200-210 (2001)
DOI: https://doi.org/10.1007/3-540-45868-9_17