Jean-Pierre Chevallet

French National Centre for Scientific Research, Lutetia Parisorum, Île-de-France, France

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Publications (93)3.54 Total impact

  • Mohannad ALMasri, Catherine Berrut, Jean-Pierre Chevallet
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    ABSTRACT: We deal, in this paper, with the short queries (containing one or two words) problem. Short queries have no sufficient information to express their semantics in a non ambiguous way. Pseudo-relevance feedback (PRF) approach for query expansion is useful in many Information Retrieval (IR) tasks. However, this approach does not work well in the case of very short queries. Therefore, we present instead of PRF a semantic query enrichment method based on Wikipedia. This method expands short queries by semantically related terms extracted from Wikipedia. Our experiments on cultural heritage corpora show significant improvement in the retrieval performance.
    Proceedings of the sixth international workshop on Exploiting semantic annotations in information retrieval; 10/2013
  • Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
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    ABSTRACT: Exhaustivity and Specificity in logical Information Retrieval framework were introduced by Nie [16]. However, even with some attempts, they are still theoretical notions without a clear idea of how to be implemented. In this study, we present a new approach to deal with them. We use propositional logic and lattice theory in order to redefine the two implications and their uncertainty P(d → q) and P(q → d). We also show how to integrate the two notions into a concrete IR model for building a new effective model. Our proposal is validated against six corpora, and using two types of terms (words and concepts). The experimental results showed the validity of our viewpoint, which state: the explicit integration of Exhaustivity and Specificity into IR models will improve the retrieval performance of these models. Moreover, there should be a type of balance between the two notions.
    Fourth International Conference on the Theory of Information Retrieval (ICTIR 2013); 09/2013
  • Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
    24th International Conference on Database and Expert Systems Applications (DEXA 2013); 08/2013
  • Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
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    ABSTRACT: Logic-based Information Retrieval (IR) models represent the retrieval decision as a logical implication d->q between a document d and a query q, where d and q are logical sentences. However, d->q is a binary decision, we thus need a measure to estimate the degree to which d implies q, denoted P(d->q). In this study, we revisit the Van Rijsbergen's assumptions about: 1- the logical implication ->' is not the material one, and 2- P(d->q) could be estimated by the conditional probability P(q|d). More precisely, we claim that the material implication is an appropriate implication for IR, and also we mathematically prove that replacing P(d->q) by P(q|d) is a correct choice. In order to prove the Van Rijsbergen's assumption, we use the Propositional Logic and the Lattice theory. We also exploit the notion of degree of implication that is proposed by Knuth.
    36th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'13); 07/2013
  • Philippe Mulhem, Jean-Pierre Chevallet
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    ABSTRACT: This paper focuses on the retrieval of parts of structured document called doxels. We propose a notion of reading context of a doxel and we exploit it to extend an Indexing Language Model (LM) with Dirichlet smoothing. We interpret a context of a doxel as a propagation of the content of the connected doxels via document structure links. We experiment this model on INEX corpus 2009, and test different context propagations. We measure a significant increase in results using contexts, compared to a reference approach without the use of context for 3 types of doxels. Moreover, our proposal outperforms the best result obtained for the Focused evaluation for the Ad Hoc task at INEX 2009.
    Proceedings of the 10th Conference on Open Research Areas in Information Retrieval; 05/2013
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    Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
    CLEF (Online Working Notes/Labs/Workshop); 09/2012
  • Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
    23rd International Conference on Database and Expert Systems Applications (DEXA 2012); 09/2012
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    Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
    CLEF 2011 Labs and Workshop, Notebook Papers; 09/2011
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    Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut
    COnférence en Recherche d'Infomations et Applications - CORIA 2011, 8th French Information Retrieval Conference; 03/2011
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    Philippe Mulhem, Jean-Pierre Chevallet
    COnférence en Recherche d'Infomations et Applications - CORIA 2010, 7th French Information Retrieval Conference, Sousse, Tunisia, March 18-20, 2010. Proceedings; 01/2010
  • Loïc Maisonnasse, Catherine Berrut, Jean-Pierre Chevallet
    Document numérique 03/2009; 12(1). DOI:10.3166/dn.12.1.107-128
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    ABSTRACT: The ubiquity of camera phones provides a convenient platform to develop immersive mixed-reality games. In this paper we introduce such a game which is loosely based on the popular card game “Memory”, where players are asked to match a pair of identical cards among a set of overturned cards by revealing only two cards at a time. In our game, the players are asked to match a “digital card”, which corresponds to a scene in a virtual world, to a “physical card”, which is an image of a scene in the real world. The objective is to convey a mixed-reality sensation. Cards are matched with a scene identification engine which consists of multiple classifiers trained on previously collected images. We present our comprehensive overall game design, as well as implementation details and results. We also describe how we constructed our scene identification engine and its performance. Finally, we present an analysis of player surveys to gauge the potential market acceptance.
    The Visual Computer 01/2009; 25(1):25-37. DOI:10.1007/s00371-008-0283-3 · 1.07 Impact Factor
  • Philippe Mulhem, Jean-Pierre Chevallet
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    ABSTRACT: We present in this paper the work of the Information Retrieval Modeling Group (MRIM) of the Computer Science Laboratory of Grenoble (LIG) at the INEX 2009 Ad Hoc Track. Our aim this year was to twofold: first study the impact of extracted noun phrases taken in addition to words as terms, and second using forward links present in Wikipedia to expand queries. For the retrieval, we use a language model with Dirichlet smoothing on documents and/or doxels, and using an Fetch and Browse approach we select rank the results. Our best runs according to doxel evaluation get the first rank on the Thorough task, and according to the document evaluation we get the first rank for the Focused, Relevance in Context and Best in Context tasks.
    Focused Retrieval and Evaluation, 8th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2009, Brisbane, Australia, December 7-9, 2009, Revised and Selected Papers; 01/2009
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    ABSTRACT: This paper describes mainly the experiments that have been conducted by the MRIM group at the LIG in Grenoble for the the ImageCLEF 2009 campaign, focusing on the work done for the Robotvision task. The proposal for this task is to study the behaviour of a generative approach inspired by the language model of information retrieval. To fit with the specificity of the Robotvision task, we added post-processing in a way to tackle with the fact that images do belong only to several classes (rooms) and that image are not independent from each others (i.e., the robot cannot in one second be in three different rooms). The results obtained still need improvement, but the use of such language model in the case of Robotvision is showed. Some results related to the Image Retrieval task and the Image annotation task are also presented.
    Multilingual Information Access Evaluation II. Multimedia Experiments - 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009, Corfu, Greece, September 30 - October 2, 2009, Revised Selected Papers; 01/2009
  • Loïc Maisonnasse, Catherine Berrut, Jean-Pierre Chevallet
    Actes du XXVIème Congrès INFORSID, Fontainebleau, France, 27 au 30 mai 2008; 01/2008
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    Ali Mustafa Qamar, Éric Gaussier, Jean-Pierre Chevallet, Joo-Hwee Lim
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    ABSTRACT: We propose in this paper an algorithm for learning a general class of similarity measures for kNN classification . This class encompasses, among others, the standard co- sine measure, as well as the Dice and Jaccard coefficients. The algorithm we propose is an extension of the voted per- ceptron algorithm and allows one to learn different types of similarity functions (either based on diagonal, symmet- ric or asymmetric similarity matrices). The results we ob- tained show that learning similarity measures yields signi f- icant improvements on several collections, for two predic- tion rules: the standard kNN rule, which was our primary goal, and a symmetric version of it.
    Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), December 15-19, 2008, Pisa, Italy; 01/2008
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    [Show abstract] [Hide abstract]
    ABSTRACT: The ubiquity of camera phones provides a convenient platform to develop immersive mixed-reality games. In this paper we introduce such a game which is loosely based on the popular card game “Memory”, where players are asked to match a pair of identical cards among a set of overturned cards by revealing only two cards at a time. In our game, the players are asked to match a “physical card”, which is an image of a scene in the real world, to a “digital card”, which corresponds to a scene in a virtual world. The objective is to convey a mixed-reality sensation. Cards are matched with a scene identification engine which consists of multiple classifiers trained on previously collected images. We present our comprehensive overall game design, as well as implementation details and results. Additionally, we also describe how we constructed our scene identification engine and its performance.
    Advances in Multimedia Modeling, 14th International Multimedia Modeling Conference, MMM 2008, Kyoto, Japan, January 9-11, 2008, Proceedings; 01/2008
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    ABSTRACT: With the current trend, we can anticipate that future mobile phones will have ever-increasing computational power and be able to embed several captors/effectors including cameras, GPS, orientation sensors, tactile surfaces and vibro-tactile display. Such powerful mobile platforms enable us to deploy mixed reality systems. Many studies on mobile mixed reality focus on games. In this paper, we describe the deployment and a user study of a mixed reality location-based mobile treasure hunt, Snap2Play[1], using technologies such as place recognition, accelerometers and GPS tracking for enhancing the interaction with the game and therefore the game playability. The game that we deployed and tested is running on an off-the-shelf camera phone.
    Proceedings of the 10th Conference on Human-Computer Interaction with Mobile Devices and Services, Mobile HCI 2008, Amsterdam, the Netherlands, September 2-5, 2008; 01/2008
  • Saïd Radhouani, Gilles Falquet, Jean-Pierre Chevallet
    Database and Expert Systems Applications, 19th International Conference, DEXA 2008, Turin, Italy, September 1-5, 2008. Proceedings; 01/2008

Publication Stats

436 Citations
3.54 Total Impact Points

Institutions

  • 2006–2013
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France
  • 2010
    • Laboratoire d'Informatique de Grenoble
      Grenoble, Rhône-Alpes, France
  • 2009
    • Université Pierre Mendès France - Grenoble 2
      Grenoble, Rhône-Alpes, France
  • 2005–2008
    • Institute for Infocomm Research
      • Department of Human Language Technology
      Tumasik, Singapore
  • 1970
    • University of Grenoble
      Grenoble, Rhône-Alpes, France