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A strategy of multi-criteria decision-making task ranking in social-networks

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Abstract

In this paper, we formulate an interesting problem of multicriteria decision-making task ranking in social networks (MCDM-TR). MCDM-TR contains two phases: (1) finding a set of decision-making experts for tasks who not only complete the decision-making of the given task but also have the minimal communication cost among them; (2) ranking the decision-made tasks according to a certain decision standard. In this paper, we focus on these two phases and propose an efficient algorithm for multicriteria decision-making tasks in social networks. A case study of academic conferences quality evaluation system (ACQES) is also studied to illustrate our strategy.

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Notes

  1. www.arnetminer.org.

  2. http://arnetminer.org/lab-datasets/expertfinding/.

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Authors and Affiliations

  1. China Telecom, Jiangsu Branch, Nanjing, China

    Zhiyuan Shi

  2. Korea Advanced Institute of Science and Technology, Daejeon, South Korea

    Fei Hao

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  1. Zhiyuan Shi
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  2. Fei Hao
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Correspondence to Zhiyuan Shi.

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Shi, Z., Hao, F. A strategy of multi-criteria decision-making task ranking in social-networks. J Supercomput 66, 556–571 (2013). https://doi.org/10.1007/s11227-013-0934-7

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