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Travelled to:
1 × Chile
1 × China
1 × France
1 × Portugal
1 × Spain
1 × Switzerland
3 × USA
Collaborated with:
R.Perego S.Orlando D.Ceccarelli F.M.Nardini F.Silvestri S.Trani S.Gordea N.Tonellotto R.Venturini M.Boley D.Paurat T.Gärtner R.Blanco H.Vahabi G.Tolomei R.Baraglia M.Serranó
Talks about:
recommend (3) document (3) entiti (3) rank (3) pattern (2) explain (2) system (2) search (2) random (2) queri (2)

Person: Claudio Lucchese

DBLP DBLP: Lucchese:Claudio

Contributed to:

SIGIR 20152015
CIKM 20142014
CIKM 20132013
SAC 20132013
CIKM 20122012
ECIR 20122012
KDD 20112011
TPDL 20112011
SAC 20102010
SAC 20062006

Wrote 11 papers:

SIGIR-2015-LuccheseNOPT #documentation #ranking
Speeding up Document Ranking with Rank-based Features (CL, FMN, SO, RP, NT), pp. 895–898.
SIGIR-2015-LuccheseNOPTV #algorithm #documentation #named #performance #rank
QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees (CL, FMN, SO, RP, NT, RV), pp. 73–82.
CIKM-2014-TraniCLOP #documentation
Manual Annotation of Semi-Structured Documents for Entity-Linking (ST, DC, CL, SO, RP), pp. 2075–2077.
CIKM-2013-CeccarelliLOPT #learning #metric
Learning relatedness measures for entity linking (DC, CL, SO, RP, ST), pp. 139–148.
SAC-2013-CeccarelliGLNP #query #recommendation #semantics
When entities meet query recommender systems: semantic search shortcuts (DC, SG, CL, FMN, RP), pp. 933–938.
CIKM-2012-BlancoCLPS #exclamation #recommendation #why
You should read this! let me explain you why: explaining news recommendations to users (RB, DC, CL, RP, FS), pp. 1995–1999.
ECIR-2012-LucchesePSVV #how #random
How Random Walks Can Help Tourism (CL, RP, FS, HV, RV), pp. 195–206.
KDD-2011-BoleyLPG #performance #random
Direct local pattern sampling by efficient two-step random procedures (MB, CL, DP, TG), pp. 582–590.
TPDL-2011-CeccarelliGLNT #experience #query #using
Improving Europeana Search Experience Using Query Logs (DC, SG, CL, FMN, GT), pp. 384–395.
SAC-2010-LuccheseOP #dataset #generative #mining
A generative pattern model for mining binary datasets (CL, SO, RP), pp. 1109–1110.
SAC-2006-BaragliaLOSS #privacy #recommendation #web
A privacy preserving web recommender system (RB, CL, SO, MS, FS), pp. 559–563.
Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.