Large scale distributed INDexation of multimedia Objects


LINDO regards the indexing, storage and retrieval of multimedia objects and studies distributed architectures and indexes (e.g., of metadata, content descriptors, ...) for high-volume data and efficient transfer of the data. The indexes also regard the necessary data in order to accurately answer questions posed in natural language to the repositories. The question answering aspect, in addition, requires technologies for the analysis of the natural language questions and their mapping to the content representations, which are in the form of topic maps (ISO/IEC 13250).


The LINDO Partners are: Thales Security Systems, CEA List , SUPELEC (Prof. Olivier Pietquin), IRIT ( Prof. Florence Sèdes), SGT, Space Applications Services, Hi-Stor Technologies, DENODO, Telefonica Investigacion y Desarolla , and Infoglobal .


We have drafted a comprehensive state-of-the-art on question answering and have developed technologies for the analysis of the natural language questions and query statements, where we have focused on the recognition and normalization of temporal expressions. This technology is integrated in a demonstrator built in the domain of surveillance videos.

Period From 2007-11-01 to 2010-10-31.
Financed by Information Technology for European Advancement - EU ITEA 2 (06011) and the Instituut voor de Aanmoediging van Innovatie door Wetenschap en Technologie in Vlaanderen - IWT 070043
Supervised by Marie-Francine Moens
Staff Oleksandr Kolomiyets
Contact Oleksandr Kolomiyets

More information can be found on the project website


  1. MOENS, Marie-Francine & SAINT-DIZIER, P. (Eds.) Knowledge and Reasoning for Answering Questions. Workshop Proceedings, International Conference On Computational Linguistics (COLING 2008). Stroudsburg, PA: Association for Computational Linguistics. 2008
  2. KOLOMIYETS, Oleksandr & MOENS, Marie-Francine Meeting TempEval-2: Shallow Approach for Temporal Tagging. In Proceedings of the NAACL-HLT Workshop on Semantic Evaluations: Recent Advances and Future Directions. Association for Computational Linguistics. 2009
  3. KOLOMIYETS, Oleksandr & MOENS, Marie-Francine Machine Learning Approaches for Temporal Information Extraction. In Fourth International Workshop on Applications of Semantic Technologies (AST'09). 2009
  4. DIZIER, P. & MOENS, M.-F. Knowledge and Reasoning for Answering Questions. Workshop Proceedings (KRAQ 2009). Association for Computational Linguistics. 2009
  5. MOENS, Marie-Francine De slimme machine die kennis vergaart uit tekst. Karakter, 28, 19-21. 2009
  6. KOLOMIYETS, O. & MOENS, M.-F. Recent Advances in Temporal Processing of Text. In Proceedings CLIN 20 Meeting. Utrecht University. 2010
  7. KOLOMIYETS, Oleksandr, BETHARD, Steven & MOENS, Marie-Francine Model-Portability Experiments for Textual Temporal Analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (pp. 271-276). ACL. 2011
  8. SAINT-DIZIER, Patrick & MOENS, Marie-Francine, Knowledge and Reasoning for Question Answering: Research Perspectives. Information Processing & Management, 47 (6), 899-906. 2011
  9. KOLOMIYETS, Oleksandr and MOENS, Marie-Francine A Survey on Question Answering Technology from an Information Retrieval Perspective. Information Sciences (in press). 2011
  10. MOENS, Marie-Francine & SAINT-DIZIER, Patrick Introduction to the Special Issue on Question Answering. Information Processing & Management, 47 (6), 805-807. 2011
  11. BENAMARA, F., MOENS, M.-F, SAINT-DIZIER, P. (Eds.) Knowledge and Reasoning for Answering Questions. Proceedings IJCAI 2005 Workshop Edinburgh. 2005

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