Claudio Lucchese
Ca' Foscari University of Venice
163 Papers
811 Citations
Claudio Lucchese is an academic researcher from Ca' Foscari University of Venice. The author has contributed to research in topics: Computer science & Learning to rank. The author has an hindex of 29, co-authored 136 publications. Previous affiliations of Claudio Lucchese include National Research Council & Istituto di Scienza e Tecnologie dell'Informazione.
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Papers
On closed constrained frequent pattern mining
Francesco Bonchi,Claudio Lucchese +1 more
- 01 Nov 2004
TL;DR: This paper provides a formal definition of constrained frequent patterns and shows how to combine the most recent results in both paradigms, providing a very efficient algorithm which exploits the two requirements together at mining time in order to reduce the computation as much as possible.
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Building a web-scale image similarity search system
Michal Batko,Fabrizio Falchi,Claudio Lucchese,David Novak,Raffaele Perego,Fausto Rabitti,Jan Sedmidubsky,Pavel Zezula +7 more
TL;DR: The experience in building an experimental similarity search system on a test collection of more than 50 million images and the performance of this technology and its evolvement as the data volume grows by three orders of magnitude is studied.
Document Similarity Self-Join with MapReduce
Ranieri Baraglia,Gianmarco De Francisci Morales,Claudio Lucchese +2 more
- 13 Dec 2010
TL;DR: This paper focuses on document collections, which are characterized by a sparseness that allows effective pruning strategies, and proposes a new parallel algorithm within the MapReduce framework that outperforms the state of the art by a factor 4.5.
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Pushing tougher constraints in frequent pattern mining
Francesco Bonchi,Claudio Lucchese +1 more
- 18 May 2005
TL;DR: A new class of tough constraints, namely Loose Anti-monotone constraints, are introduced, and it is shown how these constraints can be exploited in a level-wise Apriori-like computation by means of a new data-reduction technique.
QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees
Claudio Lucchese,Franco Maria Nardini,Salvatore Orlando,Raffaele Perego,Nicola Tonellotto,Rossano Venturini +5 more
- 09 Aug 2015
TL;DR: This paper presents QuickScorer, a new algorithm that adopts a novel bitvector representation of the tree-based ranking model, and performs an interleaved traversal of the ensemble by means of simple logical bitwise operations.
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