Philippe Mulhem
Scholar

Philippe Mulhem

Google Scholar ID: _NlUevwAAAAJ
LIG-CNRS
Computer ScienceInformation Retrieval
Citations & Impact
All-time
Citations
424
 
H-index
11
 
i10-index
14
 
Publications
20
 
Co-authors
0
 
Contact
Resume (English only)
Academic Achievements
  • Co-organizer of CLEF 2024 conference (Grenoble, September 9–12, 2024)
  • Co-organizer of LongEval CLEF 2024 campaign
  • Published ECIR 2024 paper: 'LongEval: Longitudinal Evaluation of Model Performance at CLEF 2024'
  • Program co-chair of CORIA 2024 (French IR conference, La Rochelle)
  • Presented two papers at CORIA 2024 on collection impact and visual exploration tools for longitudinal IR evaluation
  • Publications available on HAL, LIG website, DBLP, and Google Scholar
Research Experience
  • CNRS Researcher at Laboratoire d’Informatique de Grenoble (LIG)
  • Head of the MRIM research team
  • Worked until October 2016 on integrating language models on graphs for photograph description, in collaboration with Globe VIP
  • Participated in multimedia indexing and retrieval evaluation campaigns: NTCIR Lifelogging, CLEF Image Annotation
  • Co-managed (with Lorraine Goeuriot) a CLEF Tweet Contextualization Lab task on evaluating tweet indexing/retrieval quality from festivals
  • Co-proposed (with Yves Chiaramella and Franck Fourel) the “Fetch&Browse” framework for structured multimedia document retrieval, influential in INEX campaigns (2003–2010)
Background
  • Information Retrieval Researcher
  • Works on modeling and experimenting with indexing and retrieval of text and visual data
  • Currently focuses on continuous evaluation of Web search engines in the Kodicare project
  • Also works on explainable video retrieval
  • Collaborates with Schneider Electric on indexing and retrieval of normative documents
  • Previously focused on theoretical IR models (e.g., using Jensen-Shannon divergences) and hypotheses like the Document-Document Matching Constraint
  • Investigates whether such constraints apply to continuous representations (e.g., LDA, LSA, deep learning)
Co-authors
0 total
Co-authors: 0 (list not available)