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Annalisa
Appice' Home Page
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.
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Annalisa Appice
PhD in Computer Science
Associate Professor
Dipartimento
di Informatica
Universitŕ
degli Studi di Bari
Via Orabona 4
70126 Bari - Italy
phone: +39 080 5443262
fax: +39 080 5443269
email: appice@di.uniba.it
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Curriculum
Vitae et Studiorum
General Info
Nationality:
Italian
Education
- January 2007 - March 2007 - She was visiting researcher of
the Department of Knowledge Technologies of Jozef Stefan Institute (Ljubljana, Slovenia) under supervision of Prof. Saso Dzeroski.
- November 2003 - February 2004 - She was visiting student of
the Machine Learning Group headed by Prof. Peter Flach
at Department of Computer Science, University of Bristol, UK.
- March 2003 - She attended the advanced course On New Frontiers Of Information Society
Technologies held in Turin (Italy)
- August 2002 - She attended the EDBT’02 Summer School on
Distributed Databases on the Net: Models, Languages and Infrastructures
held in Cargese (Corsica, France)
- August 2002 - She attended the Summer School on Relational Data Mining Summer School
held in Helsinki (Finland).
- November 2001 – March 2005 She has been employed as PhD
student under the supervision of Prof. Donato Malerba at the
Department of Informatics, University of Bari. She defended her Ph.D.
Thesis in 2005.
- March 2001 - She received a Laurea Degree with full
marks and honors in Computer Science from the University of Bari. She
discussed a thesis on "Knowledge discovery in relational database:
Experimental results on the effects of the simplification techniques on
model trees induced with SMOTI"..
Awards
- September 2005 She received a special mention
within AI*IA 2005 for the scientific curriculum vitae and the ph.D
dissertation entitled “Learning
Relational Model Trees”.
- March 2002 - She received an award from University of
Bari as best student in the Faculty of Mathematics, Sciences and Physics
in 2000/2001
Research Projects
- IST-1999-10536 project SPIN! “Spatial Mining on Data of
Public Interest”, 2000-2002.
- IST-2000-25161 project ASSO “Analysis System of Symbolic Official data”, 2001-2003.
- KDubiq project “A Blueprint for Ubiquitous Knowledge
Discovery Systems”, 2005-2008.
- DIPIS strategic project supported by Apulia Region “Produzione Distribuita come Sistema Innovativo (Distributed Production as Innovative System), 2007-2009.
- DDTA project supported by "Dipartimento per Innovazione e Tecnologie"(Department for Innovation and Technology) “ Distretti Digitali del Tessile-Abbigliamento, 2006-2008.
- TOCAI.IT project “Tecnologie Orientate alla Conoscenza per Aggregazioni di Imprese in InterneT“, 2006-2008.
- COFIN 1998 project “Agenti Intelligenti: Interazione e Acquisizione di Conoscenza”
(Intelligent Agents: Interaction and Knowledge Acquisition), 1999-2000
- COFIN 1999 project “Modelli Statistici di Classificazione e di
Segmentazione per l'Analisi di Dati Strutturati in Forma Complessa:
Metodologie, Software e Applicazioni” (Statistical
Models for Classification and Segmentation of Complex Data Structures:
Methodologies, Software and Applications), 2000-2001
- COFIN 2001 project “Metodi di estrazione, di validazione e di
rappresentazione dell'informazione statistica in un contesto decisionale”
(Methods of knowledge discovery, validation and representation of the
statistical information in decision tasks), 2002-2003
- ATENEO 2002 “Scoperta
di conoscenza in basi di dati: metodi e tecniche efficienti e robuste per
dati complessi” (Knowledge discovery in database: efficient methods and
techniques for complex data)
- ATENEO 2003 “Metodi
di apprendimento automatico e di data mining per sistemi di conoscenza
basati sulla semantica” (Methods of machine learning and data mining
semantic based knowledge systems)
- ATENEO 2004 “Metodi
di Data Mining Multi-relazionale per la scoperta di conoscenza in basi di
dati” (Methods for multi-relational for knowledge discovery in databases)
- ATENEO 2005
“Gestione dell'informazione non strutturata: modelli, metodi e
Architetture” (Unstructured Information management: models, methods and
architectures)
- ATENEO 2006 “Metodi
di scoperta di conoscenza per ubiquitous computing” (Knowledge Discovery
Methods for ubiquitous
computing)
- ATENEO 2007 “Metodi di scoperta della conoscenza nelle basi di dati: evoluzioni rispetto allo schema unimodale” (Knowledge Discovery
in databases: extensions with respect to the unimodal schema)
- ATENEO 2008 “Scoperta di conoscenza in domini relazionali” (Knowledge Discovery
in relational domains)
- ATENEO 2009 “Estrazione, Rappresentazione e Analisi di Dati Complessi” (Extraction, Representation and Analysys of Complex Data)
Activities
Program Committee Membership of:
- AAAI Conference on Artificial Intelligence
( AAAI 2010)
- The International Conference on Machine Learning(
ICML 2010)
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining(
KDD 2010)
- The European Conference on Machine Learning/European Conference on Principles and Practice of Knowledge Discovery and Databases(
ECML 2007, ECML 2008, ECML 2009, ECML 2010)
- The IEEE International Conference on Data Mining (
ICDM 2008, ICDM 2009, ICDM 2010)
- The International Conference on Inductive Logic Programming (
ILP 2008,
ILP 2009,
ILP 2010)
- The ACM Symposium on Applied Computing - Data Mining Track (SAC 2008, SAC 2009,
SAC 2010)
- The International Conference on Database and Expert Systems Applications
(DEXA 2009, DEXA 2010)
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- The Pacific-Asia Conference on Knowledge Discovery and Data Mining
(PAKDD 2009)
- The Asian Conference on Machine Learning
(ACML 2009)
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The International Database Engineering & Applications Symposium
(IDEAS 2009)
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International Conference on Advances in Databases (DB 2009 ,
DBKDA 2010 )
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The the Mexican International Conference on Computer Science
(ENC 2009)
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The Mexican International Conference on Artificial Intelligence
(MICAI 2009)
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The IADIS MultiConference on Computer Science and Information Systems - Data Mining (ECDM 2007, ECDM 2008,
ECDM 2009, ECDM 2010)
-
The IASTED International Conference on Advances in Computer Science and Engineering
(ACSE 2009,
ACSE 2010)
-
The International conference on digital information management
(ICDIM 2009)
-
The International Conference on Artificial Intelligence: Methodology, Systems, Applications
(AIMSA 2008, AIMSA 2010)
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The International Workshop on Spatial and Spatiotemporal Data Mining
(SSTDM 2008,SSTDM 2009)
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The International Workshop on Defence against Spam in Electronic Communication
(DaSECo 2009,DaSECo 2010)
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International Workshop on Interesting Knowledge Mining – IKM 2009
(IKM 2009, IKM 2010)
- IEA/AIE 2009 Special Session on Mining Interesting Knowledge (MIK)
- Symbolic and Spatial Data Analysis: Mining Complex Data Structures”co-located with the 15th European Conference on Machine
Learning (ECML) and the 8th European Conference on Principles and Practice of
Knowledge Discovery in Databases (PKDD)
International Reviewers Committee Member of:
- International Conference on Knowledge-Based and Intelligent Information and Engineering Systems( KES 2008 )
She acted as a referee of several international journals ( Machine Learning ,
International Journal of Data Mining, Modelling and Management (IJDMMM),
International Journal of Geographical Information Science (IJGIS),
Information Sciences,
AACM Transactions on Knowledge Discovery from Data,
Fundamenta Informaticae,
Pattern Recognition Letters ,
Data and Knowledge Engineering (DKE),
Knowledge and Information Systems (KAIS),
Journal of Science and Engineering (TKJSE),
International Journal of Computers and Applications ...) and conferences.
She has participated to the organization of:
Multi-Relational Data Mining (MRDM 2007) co-located with the 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (as co-chair)
She has served in the organizing
committee of:
She has participated as speaker in the
tutorial on “Knowledge Mining by Symbolic Data Analysis and the Sodas Sofware”
organized by Paola Brito and Edwin Diday in conjunction with IFCS 2006 Conference Data
Science and Classification, Ljubljana, Slovenia, July 25 - 29, 2006. She
has presented a work on “Dissimilarity and Matching”.
Affiliations
- 2003-present: member of the Italian Association for
Artificial Intelligence, AI*IA
Publications
Annalisa Appice at Google Scholar
Publications listed in DBLP
Publications listed in SCOPUS
Journal papers
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)
DOI: https://doi.org/10.1016/j.eswa.2022.117144
Giuseppina Andresini, Annalisa Appice, Daniele Iaia, Donato Malerba, Nicolň Taggio, Antonello Aiello:
Leveraging autoencoders in change vector analysis of optical satellite images. J. Intell. Inf. Syst. 58(3): 433-452 (2022)
DOI: https://doi.org/10.1007/s10844-021-00670-9
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)
DOI: https://doi.org/10.1007/s10994-021-06062-y
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)
DOI: https://doi.org/10.1007/s10618-021-00792-2
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)
DOI: https://doi.org/10.1007/s10844-021-00656-7
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)
DOI: https://doi.org/10.1016/j.future.2021.04.017
Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Autoencoder-based deep metric learning for network intrusion detection. Inf. Sci. 569: 706-727 (2021)
DOI: https://doi.org/10.1016/j.ins.2021.05.016
Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Nearest cluster-based intrusion detection through convolutional neural networks. Knowl. Based Syst. 216: 106798 (2021)
DOI: https://doi.org/10.1016/j.knosys.2021.106798
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: 184073-184 (2020)
DOI: https://doi.org/10.1109/ACCESS.2020.3029323
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, 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
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
accepted version
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
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
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
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
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, 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, 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
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, 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
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
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
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, 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
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
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, 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
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, 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
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
For more information,
please do not hesitate to email me.
Ph.D Thesis
Software
KDB2000:
A KDD support system
ARES:
Association Rule Extractor from Spatial data
SONN: a Symbolic Object K-NN classifier
MuReNA: a MUlti-RElatioNA data mining system
CORSO: Custering Of Related Structured Objects
SUMATRA -TRECI: COUNT-BASED WINDOW TREND CLUSTER discovery: Summarization and Interpolation
SWOD: SLIDING WINDOW INCREMENTAL TREND CLUSTER discovery: Outlier Detection and Classification
ICT_TICT: (Time-evolving) Interpolative Clustering Tree Learners
S2TEC: Spectral and Spatio-relational Transductive Ensemble of Classifiers
S2COTRAC: Spectral-Spatial Co-Training Algorithm for the Transductive Classification of Hyperspectral Imagery Data
CVAR: cVAR (Spatio-temporal Cluster-based Vector AutoRegressive model)
CoSTK: CoSTK (CoKriging based Spatio-Temporal Interpolate)
CoNeRa: CoNeRa (COllective NEtwork Regression via Active learning)
SoCRATE: SoCRATE (Spectral-spatial CoRrelation SegmenTation based ClAssifier)
Kometa KDDE: Software -- Kometa
Courses
PhD Courses
Academic year 2016-2017
Process Mining - Bari Academic Years 16/17
Academic year 2015-2016
Stream Data Mining - Bari Academic Years 15/16
Academic year 2014-2015
Stream Data Mining - Bari Academic Years 14/15
Academic year 2013-2014
Data Mining - Bari Academic Years 13/14
Undergraduate Courses
Academic year 2016-2017
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Track A Academic Years 16/17
Academic year 2015-2016
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Track A Academic Years 15/16
Academic year 2014-2015
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Bari Academic Years 14/15
Academic year 2013-2014
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Bari Academic Years 13/14
Informatics (Informatica) Fisica - Bari Academic Years 13/14
Academic year 2012-2013
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Bari Academic Years 12/13
Academic year 2011-2012
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Bari Academic Years 11/12
Academic year 2010-2011
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Bari Academic Years 10/11
Academic year 2009-2010
Algorithms and Data Structures Lab (Laboratorio di Algoritmi e Strutture Dati) - Bari (TPS) Academic Years 09/10
Programming Languages (Informatica: Linguaggi) - Bari (Laurea Triennale in Fisica) Academic Years 09/10
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Bari Academic Years 09/10
Academic year 2008-2009
Advanced Computer Programming Methods (Metodi Avanzati di Programmazione) Informatica - Brindisi Academic Years 08/09