Person: Patrick Gallinari

DBLP: Gallinari:Patrick

Contributed to:

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Wrote 36 papers:

RecSys-2015-Guardia-Sebaoun #modelling #performance #recommendation

Latent Trajectory Modeling: A Light and Efficient Way to Introduce Time in Recommender Systems (ÉGS, VG, PG), pp. 281–284.

ECIR-2013-GaoDGG #modelling #relational

Latent Factor BlockModel for Modelling Relational Data (SG, LD, PG, JG), pp. 447–458.

ECIR-2013-LagnierDGG #information management #network #predict #social #using

Predicting Information Diffusion in Social Networks Using Content and User’s Profiles (CL, LD, ÉG, PG), pp. 74–85.

RecSys-2012-PradelUG #evaluation #metric #ranking

Ranking with non-random missing ratings: influence of popularity and positivity on evaluation metrics (BP, NU, PG), pp. 147–154.

CIKM-2011-GaoDG #predict

Temporal link prediction by integrating content and structure information (SG, LD, PG), pp. 1169–1174.

CIKM-2011-JacobDG #classification #corpus #multi #social #using

Classification and annotation in social corpora using multiple relations (YJ, LD, PG), pp. 1215–1220.

ECIR-2011-BuffoniTG #ranking

The Importance of the Depth for Text-Image Selection Strategy in Learning-To-Rank (DB, ST, PG), pp. 743–746.

ECIR-2011-Dulac-ArnoldDG #approach #classification

Text Classification: A Sequential Reading Approach (GDA, LD, PG), pp. 411–423.

ICML-2011-BuffoniCGU #learning #standard

Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision (DB, CC, PG, NU), pp. 825–832.

DocEng-2010-SpenglerG #documentation #layout #random #web

Document structure meets page layout: loopy random fields for web news content extraction (AS, PG), pp. 151–160.

SIGIR-2010-KimAGG #clustering #documentation #multi

Multi-view clustering of multilingual documents (YMK, MRA, CG, PG), pp. 821–822.

ECIR-2009-TollariDMFAG #concept #image #retrieval #visual notation

Exploiting Visual Concepts to Improve Text-Based Image Retrieval (ST, MD, CM, AFT, MRA, PG), pp. 701–705.

ICML-2009-UsunierBG #classification #order #ranking

Ranking with ordered weighted pairwise classification (NU, DB, PG), pp. 1057–1064.

CIKM-2008-KimPAG #clustering #documentation

An extension of PLSA for document clustering (YMK, JFP, MRA, PG), pp. 1345–1346.

ICEIS-AIDSS-2007-PessiotTUAG #collaboration #learning #rank

Learning to Rank for Collaborative Filtering (JFP, TVT, NU, MRA, PG), pp. 145–151.

ICML-2007-BordesBGW #multi

Solving multiclass support vector machines with LaRank (AB, LB, PG, JW), pp. 89–96.

MLDM-2007-WisniewskiMDG #documentation #probability

Probabilistic Model for Structured Document Mapping (GW, FM, LD, PG), pp. 854–867.

ECIR-2006-VittautG #information retrieval #machine learning #ranking

Machine Learning Ranking for Structured Information Retrieval (JNV, PG), pp. 338–349.

CIKM-2005-AminiTULG #documentation #learning #using #xml

Learning to summarise XML documents using content and structure (MRA, AT, NU, ML, PG), pp. 297–298.

CIKM-2005-VuG #retrieval #using

Using RankBoost to compare retrieval systems (HTV, PG), pp. 309–310.

ECIR-2005-AminiUG #algorithm #automation #clustering #ranking #summary

Automatic Text Summarization Based on Word-Clusters and Ranking Algorithms (MRA, NU, PG), pp. 142–156.

ICEIS-v2-2004-FotzoG #documentation #information management #topic

Information Access via Topic Hierarchies and Thematic Annotations from Document Collections (HNF, PG), pp. 69–76.

DocEng-2003-DenoyerVGBB #classification #documentation #multi

Structured multimedia document classification (LD, JNV, PG, SB, SB), pp. 153–160.

ICDAR-2003-MarukatatSAG #flexibility #online #recognition

A Flexible Recognition Engine for Complex On-line Handwritten Character Recognition (SM, RS, TA, PG), pp. 1048–1052.

MLDM-2003-DenoyerG #categorisation #documentation #generative #xml

A Belief Networks-Based Generative Model for Structured Documents. An Application to the XML Categorization (LD, PG), pp. 328–342.

MLDM-2003-PiwowarskiG #documentation #information retrieval #machine learning

A Machine Learning Model for Information Retrieval with Structured Documents (BP, PG), pp. 425–438.

SIGIR-2002-AminiG #learning #summary #using

The use of unlabeled data to improve supervised learning for text summarization (MRA, PG), pp. 105–112.

ICDAR-2001-BelliliGG #hybrid

An Hybrid MLP-SVM Handwritten Digit Recognizer (AB, MG, PG), pp. 28–33.

ICDAR-2001-GauthierAGD #online #recognition

Strategies for Combining On-line and Off-line Information in an On-line Handwriting Recognition System (NG, TA, PG, BD), pp. 412–416.

ICDAR-2001-MarukatatAGD #hybrid #modelling #recognition

Sentence Recognition through Hybrid Neuro-Markovian Modeling (SM, TA, PG, BD), pp. 731–737.

ICPR-v2-2000-ArtieresMGD #modelling #multi #online #recognition

Multi-Modal Segmental Models for On-Line Handwriting Recognition (TA, JMM, PG, BD), pp. 2247–2250.

ACIR-1999-AminiZG #automation #information management #modelling #sequence

Sequence Models for Automatic Highlighting and Surface Information Extraction (MRA, HZ, PG).

ICDAR-1999-WimmerDG #recognition #taxonomy #word

Dictionary Preselection in a Neuro-Markovian Word Recognition System (ZW, BD, PG), pp. 539–542.

ACIR-1998-ZaragozaG #information management #information retrieval #modelling #probability

Coupled Hierarchical IR and Stochastic Models for Surface Information Extraction (HZ, PG).

ICPR-1996-Garcia-SalicettiDGW #adaptation #online #predict #recognition #word

Adaptive discrimination in an HMM-based neural predictive system for on-line word recognition (SGS, BD, PG, ZW), pp. 515–519.

ICDAR-v1-1995-Garcia-SalicettiDGMF #markov #online #predict #recognition

A hidden Markov model extension of a neural predictive system for on-line character recognition (SGS, BD, PG, AM, DF), pp. 50–53.