Titlebook: Computational Collective Intelligence; 12th International C Ngoc Thanh Nguyen,Bao Hung Hoang,Gottfried Vossen Conference proceedings 2020 S

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Topic Diffusion Prediction on Bibliographic Network: New Approach with Combination Between External the topic, which is propagated as an intrinsic factor. Finally, we amalgamate the activation probability feature and the author’s preference feature in the topic’s spreading prediction. We conducted experiments on dissimilar topics of the bibliographic network dataset and have attained satisfactory results.

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Using Interval-Valued Fuzzy Sets for Recommending Groups in E-Learning Systemsre determined taking into account similarity of their dominant features and the highest ranked attributes of groups. The presented approach is examined, for students described by learning style dimensions. The method is evaluated on the basis of experimental results obtained for data of different groups of real students.

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0302-9743 held in Da Nang, Vietnam, in November 2020.*.The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; application

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Analysis of User Story Dynamics on a Medium-Size Social News Siteowever, it turns out that still more data records and more complete and accurate measurement approach are needed in order to use the model for prediction of story popularity or to detect untrue stories.

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Collective Decision-Making as a Contextual Multi-armed Bandit Problemice to expected outcomes. In summary, our work reveals that, when trying to make the best choice in a problem with multiple alternatives, meta-CMAB assures that the collective knowledge of experts leads to the best outcome without the need for accurate confidence estimates.

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How Expert Confidence Can Improve Collective Decision-Making in Contextual Multi-Armed Bandit Problessumptions of prior work, we introduce confidence estimates and propose a novel approach to deciding with expert advice which can take advantage of these estimates. We further show that, when confidence estimates are imperfect, the proposed approach is more robust than the classical confidence-weighted majority vote.

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Structure and Physics of Virusesowever, it turns out that still more data records and more complete and accurate measurement approach are needed in order to use the model for prediction of story popularity or to detect untrue stories.