Claudio Lucchese

发表

ConQueSt: a Constraint-based Querying System for Exploratory Pattern Discovery

Salvatore Orlando, Raffaele Perego, Francesco Bonchi, 2006, 22nd International Conference on Data Engineering (ICDE'06).

Evaluating Top-K Approximate Patterns via Text Clustering

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2016, DaWaK.

Mining Top-K Patterns from Binary Datasets in Presence of Noise

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2010, SDM.

The Impact of Negative Samples on Learning to Rank

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2017, LEARNER@ICTIR.

Right-Protected Data Publishing with Provable Distance-Based Mining

Claudio Lucchese, Michail Vlachos, Spyros I. Zoumpoulis, 2014, IEEE Transactions on Knowledge and Data Engineering.

Pornography consumption in Social Media pdf

Fabrizio Silvestri, Claudio Lucchese, Mauro Coletto, 2016, ArXiv.

LEARning Next gEneration Rankers (LEARNER 2017)

Raffaele Perego, Nicola Ferro, Claudio Lucchese, 2017, ICTIR.

Discovering Europeana Users' Search Behavior

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2011, ERCIM News.

kDCI: on using direct count up to the third iteration

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2004, FIMI.

Direct local pattern sampling by efficient two-step random procedures

Daniel Paurat, Thomas Gärtner, Claudio Lucchese, 2011, KDD.

Proc. 1st International Workshop on LEARning Next gEneration Rankers (LEARNER 2017)

Raffaele Perego, Nicola Ferro, Claudio Lucchese, 2017 .

Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning

Maarten de Rijke, Rolf Jagerman, Sebastian Bruch, 2019, SIGIR.

SEL: A Unified Algorithm for Entity Linking and Saliency Detection

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2016, DocEng.

X-CLEaVER

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2018, ACM Trans. Intell. Syst. Technol..

Selective Gradient Boosting for Effective Learning to Rank

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2018, SIGIR.

Exploiting CPU SIMD Extensions to Speed-up Document Scoring with Tree Ensembles

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2016, SIGIR.

Perception of social phenomena through the multidimensional analysis of online social networks

Andrea Esuli, Raffaele Perego, Cristina Ioana Muntean, 2017, Online Soc. Networks Media.

Polarized User and Topic Tracking in Twitter

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2016, SIGIR.

X-CLE a VER: Learning Ranking Ensembles by Growing and Pruning Trees

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2018 .

Efficiency/Effectiveness Trade-offs in Learning to Rank

Franco Maria Nardini, Claudio Lucchese, F. M. Nardini, 2017, ICTIR.

RankEval: An Evaluation and Analysis Framework for Learning-to-Rank Solutions

Raffaele Perego, Cristina Ioana Muntean, Franco Maria Nardini, 2017, SIGIR.

Dexter 2.0 - an Open Source Tool for Semantically Enriching Data

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2014, International Semantic Web Conference.

Certifying Decision Trees Against Evasion Attacks by Program Analysis pdf

Pietro Ferrara, Claudio Lucchese, Stefano Calzavara, 2020, ESORICS.

Enabling Content-Based Image Retrieval in Very Large Digital Libraries

Andrea Esuli, Raffaele Perego, Fabrizio Falchi, 2009 .

On closed constrained frequent pattern mining

Francesco Bonchi, Claudio Lucchese, F. Bonchi, 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

X-DART: Blending Dropout and Pruning for Efficient Learning to Rank

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2017, SIGIR.

Boosting learning to rank with user dynamics and continuation methods

Claudio Lucchese, Maria Maistro, Raffaele Perego, 2019, Information Retrieval Journal.

Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios pdf

Claudio Lucchese, Stefano Calzavara, Salvatore Orlando, 2020, ArXiv.

(Query) History Teaches Everything, Including the Future

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2008, 2008 Latin American Web Conference.

Improving Europeana Search Experience Using Query Logs

Franco Maria Nardini, Claudio Lucchese, Sergiu Gordea, 2011, TPDL.

Adversarial Training of Gradient-Boosted Decision Trees

Claudio Lucchese, Stefano Calzavara, Gabriele Tolomei, 2019, CIKM.

Caching content-based queries for robust and efficient image retrieval

Salvatore Orlando, Raffaele Perego, Fabrizio Falchi, 2009, EDBT '09.

How Random Walks Can Help Tourism

Fabrizio Silvestri, Raffaele Perego, Claudio Lucchese, 2012, ECIR.

Parallel Traversal of Large Ensembles of Decision Trees

Salvatore Orlando, Francesco Lettich, Franco Maria Nardini, 2019, IEEE Transactions on Parallel and Distributed Systems.

Distributed Data Mining in Desktop Grids

Domenico Talia, Salvatore Orlando, Claudio Lucchese, 2008 .

Automatic controversy detection in social media: A content-independent motif-based approach

Aristides Gionis, Venkata Rama Kiran Garimella, Claudio Lucchese, 2017, Online Soc. Networks Media.

Direct Pattern Sampling with Respect to Pattern Frequency

Daniel Paurat, Thomas Gärtner, Claudio Lucchese, 2011, LWA.

On Including the User Dynamic in Learning to Rank

Raffaele Perego, Nicola Ferro, Claudio Lucchese, 2017, SIGIR.

Crawling, Indexing, and Similarity Searching Images on the Web

David Novak, Pavel Zezula, Michal Batko, 2008, SEBD.

From chatter to headlines: harnessing the real-time web for personalized news recommendation

Aristides Gionis, Gianmarco De Francisci Morales, Claudio Lucchese, 2012, WSDM '12.

Continuation Methods and Curriculum Learning for Learning to Rank

Raffaele Perego, Nicola Ferro, Claudio Lucchese, 2018, CIKM.

Electoral Predictions with Twitter: A Machine-Learning approach

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2015, IIR.

Summarizing Linked Data RDF Graphs Using Approximate Graph Pattern Mining

Claudio Lucchese, Dimitris Kotzinos, Dan Vodislav, 2016, EDBT.

A Motif-Based Approach for Identifying Controversy

Aristides Gionis, Venkata Rama Kiran Garimella, Claudio Lucchese, 2017, ICWSM.

Recommender Systems

Fabrizio Silvestri, Raffaele Perego, Cristina Ioana Muntean, 2014, Mining User Generated Content.

GPU-based Parallelization of QuickScorer to Speed-up Document Ranking with Tree Ensembles

Salvatore Orlando, Raffaele Perego, Francesco Lettich, 2016, IIR.

Fast Feature Selection for Learning to Rank

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2016, ICTIR.

High performance: closed frequent itemsets mining inspired by emerging computer architectures

Claudio Lucchese, C. Lucchese, 2008 .

Treant: training evasion-aware decision trees

Claudio Lucchese, Stefano Calzavara, Gabriele Tolomei, 2019, Data Mining and Knowledge Discovery.

Embedding and Retrieving Private Metadata in Electrocardiograms

Philip S. Yu, Suleyman Serdar Kozat, Claudio Lucchese, 2009, Journal of Medical Systems.

When entities meet query recommender systems: semantic search shortcuts

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2013, SAC '13.

QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2015, SIGIR.

QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2017, ECML/PKDD.

Ownership protection of shape datasets with geodesic distance preservation

Philip S. Yu, Claudio Lucchese, Michail Vlachos, 2008, EDBT '08.

QuickRank: a C++ Suite of Learning to Rank Algorithms

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2015, IIR.

Rights protection of trajectory datasets with nearest-neighbor preservation

Philip S. Yu, Claudio Lucchese, Michail Vlachos, 2010, The VLDB Journal.

Supervised Evaluation of Top-k Itemset Mining Algorithms

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2015, DaWaK.

Fast and memory efficient mining of frequent closed itemsets

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2006, IEEE Transactions on Knowledge and Data Engineering.

Scaling Out All Pairs Similarity Search with MapReduce

Ranieri Baraglia, Gianmarco De Francisci Morales, Claudio Lucchese, 2010, LSDS-IR@SIGIR.

On Suggesting Entities as Web Search Queries

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2013, IIR.

Learning to Rank User Queries to Detect Search Tasks

Salvatore Orlando, Franco Maria Nardini, Claudio Lucchese, 2016, ICTIR.

Discovering tasks from search engine query logs

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2013, TOIS.

RightsProtection ofTrajectory Datasets

Claudio Lucchese, Michail Vlachos, 2008 .

7th workshop on large-scale distributed systems for information retrieval (LSDS-IR'09)

Claudio Lucchese, Wai Gen Yee, Gleb Skobeltsyn, 2009, SIGF.

You should read this! let me explain you why: explaining news recommendations to users

Roi Blanco, Fabrizio Silvestri, Raffaele Perego, 2012, CIKM '12.

SELEcTor: Discovering Similar Entities on LinkEd DaTa by Ranking Their Features

Chiara Renso, Claudio Lucchese, Livia Ruback, 2017, 2017 IEEE 11th International Conference on Semantic Computing (ICSC).

Ranking Documents Effciently with QuickScorer

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2016, SEBD.

A Unifying Framework for Mining Approximate Top- $k$ Binary Patterns

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2014, IEEE Transactions on Knowledge and Data Engineering.

A generative pattern model for mining binary datasets

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2010, SAC '10.

Building a web-scale image similarity search system

David Novak, Pavel Zezula, Michal Batko, 2010, Multimedia Tools and Applications.

On the Value of Query Logs for Modern Information Retrieval

Raffaele Perego, Claudio Lucchese, Domenico Laforenza, 2006 .

Manual Annotation of Semi-Structured Documents for Entity-Linking

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2014, CIKM.

On condensed representations of constrained frequent patterns

Francesco Bonchi, Claudio Lucchese, 2005, Knowledge and Information Systems.

Mining query logs to optimize index partitioning in parallel web search engines

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2007, Infoscale.

Mining@home: toward a public‐resource computing framework for distributed data mining

Domenico Talia, Salvatore Orlando, Claudio Lucchese, 2010, Concurr. Comput. Pract. Exp..

Fast Traversal of Large Ensembles of Regression Trees

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2016, ERCIM News.

Miningchome: toward a public-resource computing framework for distributed data mining

Domenico Talia, Claudio Lucchese, Carlo Mastroianni, 2010 .

LSDS-IR'11: the 9th workshop on large-scale and distributed systems for information retrieval

Berkant Barla Cambazoglu, Claudio Lucchese, 2011, CIKM '11.

Multicore/Manycore Parallel Traversal of Large Forests of Regression Trees

Salvatore Orlando, Raffaele Perego, Francesco Lettich, 2017, 2017 International Conference on High Performance Computing & Simulation (HPCS).

Mining frequent closed itemsets out-of-core

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2006, SDM.

Caching Algorithms for Similarity Search

Salvatore Orlando, Raffaele Perego, Fabrizio Falchi, 2009, SEBD.

Improving Learning to Rank By Leveraging User Dynamics and Continuation Methods

Raffaele Perego, Nicola Ferro, Claudio Lucchese, 2020, SEBD.

Post-Learning Optimization of Tree Ensembles

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2016, IIR.

Mining@Home:Public resource Computing For Distributed Data Mining

Domenico Talia, Claudio Lucchese, Carlo Mastroianni, 2008 .

DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2004, FIMI.

On Interactive Pattern Mining from Relational Databases

Raffaele Perego, Fosca Giannotti, Francesco Bonchi, 2006, SEBD.

A metric cache for similarity search

Salvatore Orlando, Raffaele Perego, Fabrizio Falchi, 2008, LSDS-IR '08.

Modeling and predicting the task-by-task behavior of search engine users

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2013, OAIR.

Quality versus efficiency in document scoring with learning-to-rank models

Raffaele Perego, Franco Maria Nardini, Gabriele Capannini, 2016, Inf. Process. Manag..

Cracker: Crumbling large graphs into connected components

Laura Ricci, Patrizio Dazzi, Claudio Lucchese, 2015, 2015 IEEE Symposium on Computers and Communication (ISCC).

Mining Frequent Closed Itemsets from Distributed Repositories

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2005, Knowledge and Data Management in GRIDs.

Efficient and Effective Query Expansion for Web Search

Raffaele Perego, Franco Maria Nardini, Roberto Trani, 2018, CIKM.

InGeoCloudS: A Cloud-Based Platform for Sharing Geodata Across Europe

Raffaele Perego, Claudio Lucchese, Benoit Baurens, 2013, ERCIM News.

Adult content consumption in online social networks

Fabrizio Silvestri, Claudio Lucchese, Mauro Coletto, 2017, Social Network Analysis and Mining.

Ranieri Baraglia, Gianmarco De Francisci Morales, Claudio Lucchese, 2010, 2010 IEEE International Conference on Data Mining.

Post-Learning Optimization of Tree Ensembles for Efficient Ranking

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2016, SIGIR.

On the Behaviour of Deviant Communities in Online Social Networks pdf

Fabrizio Silvestri, Claudio Lucchese, Mauro Coletto, 2016, ICWSM.

Special track on Engineering Large-Scale Distributed Systems: editorial message

Fabrizio Falchi, Claudio Lucchese, 2008, SAC '08.

Query-level Early Exit for Additive Learning-to-Rank Ensembles

Raffaele Perego, Franco Maria Nardini, Claudio Lucchese, 2020, SIGIR.

Rights Protection of Trajectory Datasets

Philip S. Yu, Claudio Lucchese, Michail Vlachos, 2008, 2008 IEEE 24th International Conference on Data Engineering.

RDF Graph Summarization Based on Approximate Patterns

Claudio Lucchese, Dimitris Kotzinos, Dan Vodislav, 2015, ISIP.

Do Violent People Smile: Social Media Analysis of their Profile Pictures

Salvatore Orlando, Claudio Lucchese, Mauro Coletto, 2018, WWW.

Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2016, ACM Trans. Inf. Syst..

Twitter anticipates bursts of requests for Wikipedia articles

Salvatore Orlando, Claudio Lucchese, Gabriele Tolomei, 2013, DUBMOD '13.

SEL: A unified algorithm for salient entity linking

Salvatore Orlando, Raffaele Perego, David E. Losada, 2018, Comput. Intell..

Mining query logs to optimize index partitioning in parallel web search engines

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2007 .

Identifying task-based sessions in search engine query logs

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2011, WSDM '11.

Pushing Tougher Constraints in Frequent Pattern Mining

Francesco Bonchi, Claudio Lucchese, F. Bonchi, 2005, PAKDD.

Caching query-biased snippets for efficient retrieval

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2011, EDBT/ICDT '11.

ConQueSt: a Constraint-based Querying System for Exploratory Pattern Discovery

Salvatore Orlando, Raffaele Perego, Francesco Bonchi, 2006, 22nd International Conference on Data Engineering (ICDE'06).

Salvatore Orlando, Raffaele Perego, Fabrizio Falchi, 2012, Inf. Process. Manag..

Speeding up Document Ranking with Rank-based Features

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2015, SIGIR.

Fast Connected Components Computation in Large Graphs by Vertex Pruning

Laura Ricci, Patrizio Dazzi, Claudio Lucchese, 2017, IEEE Transactions on Parallel and Distributed Systems.

A privacy preserving web recommender system

Fabrizio Silvestri, Salvatore Orlando, Ranieri Baraglia, 2006, SAC.

WebDocs: a real-life huge transactional dataset

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2004, FIMI.

Proceedings of the 9th workshop on Large-scale and distributed informational retrieval

Claudio Lucchese, B. Barla Cambazoglu, 2011, CIKM 2011.

Computing Entity Semantic Similarity by Features Ranking pdf

Alexander Arturo Mera Caraballo, Marco A. Casanova, Chiara Renso, 2018, ArXiv.

Preserving Privacy in Web Recommender Systems

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2010 .

The 8th workshop on large-scale distributed systems for information retrieval (LSDS-IR'10)

Roi Blanco, Berkant Barla Cambazoglu, Claudio Lucchese, 2011, SIGF.

Sentiment Spreading: An Epidemic Model for Lexicon-Based Sentiment Analysis on Twitter

Dino Pedreschi, Cristina Ioana Muntean, Fosca Giannotti, 2017, AI*IA.

Speeding-up Document Scoring with Tree Ensembles using CPU SIMD Extensions

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2016, IIR.

RankEval: Evaluation and investigation of ranking models

Cristina Ioana Muntean, Franco Maria Nardini, Claudio Lucchese, 2020, SoftwareX.

Appreciation to distributed and parallel databases reviewers

Takahiro Hara, Sherif Sakr, Jun Kong, 2018, Distributed and Parallel Databases.

kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets

Fabrizio Silvestri, Salvatore Orlando, Raffaele Perego, 2003, FIMI.

Report on LEARNER 2017: 1st International Workshop on LEARning Next gEneration Rankers

Raffaele Perego, Nicola Ferro, Claudio Lucchese, 2018, SIGF.

Parallel Mining of Frequent Closed Patterns: Harnessing Modern Computer Architectures

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Searching 100M Images by Content Similarity

Raffaele Perego, Fabrizio Falchi, Fausto Rabitti, 2009, IRCDL.

Dexter: an open source framework for entity linking

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2013, ESAIR '13.

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2013, CIKM.

CoPhIR: a Test Collection for Content-Based Image Retrieval pdf

Andrea Esuli, Raffaele Perego, Fabrizio Falchi, 2009, ArXiv.

Social-Spatiotemporal Analysis of Topical and Polarized Communities in Online Social Networks

Claudio Lucchese, Mauro Coletto, C. Lucchese, 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

Detecting Task-Based Query Sessions Using Collaborative Knowledge

Raffaele Perego, Claudio Lucchese, Gabriele Tolomei, 2010, Web Intelligence/IAT Workshops.

AMEBA: An Adaptive Approach to the Black-Box Evasion of Machine Learning Models

Claudio Lucchese, Stefano Calzavara, Lorenzo Cazzaro, 2021, AsiaCCS.

Learning Early Exit Strategies for Additive Ranking Ensembles

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2021, SIGIR.

Beyond Robustness: Resilience Verification of Tree-Based Classifiers pdf

Salvatore Orlando, Claudio Lucchese, Stefano Calzavara, 2021, ArXiv.

Learning Early Exit Strategies for Additive Ranking Ensembles pdf

Salvatore Orlando, Raffaele Perego, Franco Maria Nardini, 2021, SIGIR.

EiFFFeL: Enforcing Fairness in Forests by Flipping Leaves pdf

Salvatore Orlando, Claudio Lucchese, Seyum Assefa Abebe, 2021, ArXiv.

Distributed Mining of Frequent Closed Itemsets: Some Preliminary Results

Salvatore Orlando, Raffaele Perego, Claudio Lucchese, 2005 .

Mining Frequent Closed Itemsets without Duplicates Generation

Claudio Lucchese, A. Faedo, C. Lucchese, 2004 .

A new prefabricated external thermal insulation composite board with ceramic finishing for buildings retrofitting

Claudio Lucchese, Alberto Fregni, Elisa Franzoni, 2016 .