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VWA: ViewpointS web application to assess collective knowledge building

Lemoisson Philippe, Rakotondrahaja Clarel M. H., Andriamialison Aroniaina Safidy Précieux, Sankar Harish A., Cerri Stefano A.. 2019. VWA: ViewpointS web application to assess collective knowledge building. In : Computational collective intelligence : 11th International Conference, ICCCI 2019, Hendaye, France, September 4–6, 2019, Proceedings, Part I. Nguyen Ngoc Thanh (ed.), Chbeir Richard (ed.), Exposito Ernesto (ed.), Aniorte Philippe (ed.) Trawiński Bogdan (ed.). Cham : Springer, pp. 3-15. (Lecture Notes in Computer Science, 11683) ISBN 978-3-030-28376-6 International Conference on Computational Collective Intelligence (ICCI 2019). 11, Hendaye, France, 4 September 2019/6 September 2019.

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ID595004.pdf

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ViewpointS.ICCCI.2019.04.11.pdf

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Hendaye.présentation.ICCCI.2019.pdf

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Matériel d'accompagnement : 1 diaporama (28 vues)

Abstract : Collective intelligence is one major outcome of the digital revolution, but this outcome is hardly evaluated. By implementing a topological knowledge graph (KG) in the metaphor of a brain, the ViewpointS approach attempts to trace and assess the dynamics of collaborative knowledge building. Our approach relies on a bipartite graph of resources (agents, documents, topics) and time stamped “viewpoints” emitted by human or artificial agents. These viewpoints are typed (logical, mining, subjective). User agents feed the graph with resources and viewpoints and exploit maps where resources are linked by “synapses” aggregating the viewpoints. They reversely emit feedback viewpoints which tighten or loosen the synapses along the knowledge paths. Shared knowledge is continuously elicited against the individual “systems of values” along the agents' exploitation/feedback loops. This selection process implements a rudimentary form of collective intelligence, which we assess through innovative metrics. In this paper, we present the exploitation/feedback loops in detail. We expose the mechanism underlying the reinforcement along the knowledge paths and introduce a new measure called Multi Paths Proximity inspired from the parallel neural circuits in the brain. Then we present the Web prototype VWA implementing the ViewpointS approach and set a small experiment assessing collective knowledge building on top of the exploitation/feedback loops.

Mots-clés libres : Viewpoints, Apprentissage collectif, Graphe de connaissances

Auteurs et affiliations

  • Lemoisson Philippe, CIRAD-ES-UMR TETIS (FRA)
  • Rakotondrahaja Clarel M. H., Université de Fianarantsoa (MDG)
  • Andriamialison Aroniaina Safidy Précieux
  • Sankar Harish A., National Institute of Technology, Kurukshetra (IND)
  • Cerri Stefano A., LIRMM (FRA)

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Source : Cirad-Agritrop (https://agritrop.cirad.fr/595004/)

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