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  • × author_ss:"Chrisment, C."
  1. Aboud, M.; Chrisment, C.; Razouk, R.; Sedes, F.; Soule-Dupuy, C.: Querying a hypertext information retrieval system by the use of classification (1993) 0.01 
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    Abstract
    We present in this paper a navigation approach using a combination of functionalities encountered in classification processes, Hypertext Systems and Information Retrieval Systems. its originality lies in the cooperation of these mechanisms to restrict the consultation universe, to locate faster the searched information, and to tackle the problem of disorientation when consulting the restricted Hypergraph of retrieved information. A first version of the SYRIUS system has been developed integrating both Hypertext and Information Retrieval functionalities that we have called Hypertext Information Retrieval System (H.I.R.S.). This version has been extended using classification mechanisms. The graphic interface of this new system version is presented here. Querying the system is done through common visual representation of the database Hypergraph. The visualization of the Hypergraph can be parameterized focusing on several levels (classes, links,...)
  2. Boughanem, M.; Chrisment, C.; Tamine, L.: On using genetic algorithms for multimodal relevance optimization in information retrieval (2002) 0.00 
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  3. Cabanac, G.; Chevalier, M.; Chrisment, C.; Julien, C.: Social validation of collective annotations : definition and experiment (2009) 0.00 
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    Abstract
    People taking part in argumentative debates through collective annotations face a highly cognitive task when trying to estimate the group's global opinion. In order to reduce this effort, we propose in this paper to model such debates prior to evaluating their social validation. Computing the degree of global confirmation (or refutation) enables the identification of consensual (or controversial) debates. Readers as well as prominent information systems may thus benefit from this information. The accuracy of the social validation measure was tested through an online study conducted with 121 participants. We compared their human perception of consensus in argumentative debates with the results of the three proposed social validation algorithms. Their efficiency in synthesizing opinions was demonstrated by the fact that they achieved an accuracy of up to 84%.
  4. Mothe, J.; Chrisment, C.; Dousset, B.; Alaux, J.: DocCube : Multi-dimensional visualisation and exploration of large document sets (2003) 0.00 
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    Footnote
    Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"

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