Exploiting Meta-cognitive Features for a Machine-Learning-Based One-Shot Group-Decision Aggregation-Reference-Cited by-同舟云学术

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Exploiting Meta-cognitive Features for a Machine-Learning-Based One-Shot Group-Decision Aggregation

Published:2023-10-21 Issue: Volume: Page:
ISSN:0926-2644
Container-title:Group Decision and Negotiation
language:en
Short-container-title:Group Decis Negot

Author:

Shinitzky Hilla^ORCID,Avraham Dan,Vaisman Yizhak,Tsizer Yakir,Leedon Yaniv,Shahar Yuval

Funder

Council for Higher Education

Publisher

Springer Science and Business Media LLC

Subject

Management of Technology and Innovation,Strategy and Management,General Social Sciences,Arts and Humanities (miscellaneous),General Decision Sciences

Link

https://link.springer.com/content/pdf/10.1007/s10726-023-09855-9.pdf

Reference67 articles.

1. Ackerman R (2014) The diminishing criterion model for metacognitive regulation of time investment. J Exp Psychol Gen 143(3):1349

2. Amir O, Shahar Y, Gal Y, et al. (2013) On the verification complexity of group decision-making tasks. In: First AAAI conference on human computation and crowdsourcing

3. Amir O, Amir D, Shahar Y et al. (2018) The more the merrier? Increasing group size may be detrimental to decision-making performance in nominal groups. PloS One 13(2):e0192213

4. Armstrong JS (2001) Principles of forecasting: a handbook for researchers and practitioners, vol 30. Springer Science & Business Media, Berlin

5. Aydin BI, Yilmaz YS, Li Y, et al. (2014) Crowdsourcing for multiple-choice question answering. In: Twenty-sixth IAAI conference

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