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International Conference on Collaboration Technologies

CollabTech 2018: Collaboration Technologies and Social Computing pp 3–18Cite as

Discussion Map with an Assistant Function for Decision-Making: A Tool for Supporting Consensus-Building

Part of the Lecture Notes in Computer Science book series (LNISA,volume 11000)

Abstract

In this paper, we propose a tool for supporting consensus-building in conversations with multiple participants. We call it “Discussion Map with Assistant (DMA)”. It consists of nodes and links. We classify the nodes into two types; alternatives and criteria. Alternatives represent what the participants are choosing between. Criteria are used to judge the alternatives. Each criterion contains an importance value. Each link between nodes also contains an importance value. The system estimates a ranking list of alternatives among participants from each map. We introduce a forgetting function to the model. The system also supports the decision-making process by using discussion maps from participants. It generates sentences and charts that describe the current state of the discussion. We evaluate the effectiveness of the discussion map system with DMA in a decision-making task experimentally.

Keywords

  • Discussion map
  • Decision support system
  • Consensus estimation
  • Support with charts and sentences

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Notes

  1. 1.

    Note that not all alternatives have a link. It depends on the participant that creates the DM.

  2. 2.

    The initial memory level is 100 in this formulation.

  3. 3.

    Note that three of them are hidden in this figure.

  4. 4.

    The difference of the score is 5% or less.

  5. 5.

    This is based on the average ranks among participants.

  6. 6.

    As conditions for the final decision, each discussion needs more than four alternatives and more than two criteria.

  7. 7.

    The assistant function, DMA, becomes active in five minutes although groups with our system can use the DM system from the start.

  8. 8.

    For instance, for G1, the number of alternatives with our system was 9 (19/2.11) while that without our system was 7 (21/3).

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Acknowledgment

This work was supported by JSPS KAKENHI Grant Number 17H01840.

Author information

Authors and Affiliations

  1. Department of Artificial Intelligence, Kyushu Institute of Technology, 680-4 Kawazu Iizuka, Fukuoka, 820-8502, Japan

    Ryunosuke Kirikihira & Kazutaka Shimada

Authors
  1. Ryunosuke Kirikihira
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  2. Kazutaka Shimada
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Corresponding author

Correspondence to Kazutaka Shimada .

Editor information

Editors and Affiliations

  1. Department of Informatics, The University of Electro-Communications, Chofu, Tokyo, Japan

    Dr. Hironori Egi

  2. Graduate School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Takaya Yuizono

  3. University of Chile, Santiago, Chile

    Nelson Baloian

  4. Wakayama University, Wakayama City, Japan

    Takashi Yoshino

  5. Otsuma Women’s University, Tokyo, Japan

    Satoshi Ichimura

  6. Departamento de Informatica, Universidade Nova de Lisboa, Caparica, Portugal

    Prof. Armanda Rodrigues

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Kirikihira, R., Shimada, K. (2018). Discussion Map with an Assistant Function for Decision-Making: A Tool for Supporting Consensus-Building. In: Egi, H., Yuizono, T., Baloian, N., Yoshino, T., Ichimura, S., Rodrigues, A. (eds) Collaboration Technologies and Social Computing. CollabTech 2018. Lecture Notes in Computer Science(), vol 11000. Springer, Cham. https://doi.org/10.1007/978-3-319-98743-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-98743-9_1

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