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Bayesian Co-Clustering Truth Discovery for Mobile Crowd Sensing Systems

机译：移动人群传感系统的贝叶斯共聚类真理发现

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摘要

With the proliferation of mobile devices, mobile crowd sensing (MCS) has emerged as a new data collection paradigm, which allows the crowd to act as sensors and contribute their observations about entities. Unfortunately, users with varied skills and motivations may provide conflicting information for the same entity. Existing work solves this problem by estimating user reliability and inferring the correct observations (i.e., truths). However, these methods assume that users' expertise degrees are dependent on the truths, but ignore the finer clusters that exist even in the entities with the same truths. To capture users' fine-grained reliability on different entity clusters, we propose a novel Bayesian co-clustering truth discovery model for the task of observation aggregation. This model enables us to produce a more precise estimation while taking into account the entity clusters and the user clusters. Experiments on four real-world datasets reveal that our method outperforms the state-of-the-art approaches in terms of accuracy and F1-score.
机译：随着移动设备的扩散，移动人群传感（MCS）被出现为新的数据收集范式，这使得人群充当传感器并有助于他们对实体的观察。不幸的是，具有各种技能和动机的用户可以为同一实体提供冲突的信息。通过估计用户可靠性并推断正确的观察（即，真相），现有工作通过估计和推断出来解决这个问题。然而，这些方法假设用户的专业知识学位取决于真相，但忽略了即使在具有相同真理的实体中存在的更精细的集群。为了在不同的实体集群上捕获用户的细粒度可靠性，我们向观察聚集的任务提出了一种新的贝叶斯共聚类真理发现模型。该模型使我们能够在考虑实体群集和用户群集的同时产生更精确的估计。四个真实数据集的实验表明，我们的方法在准确性和F1分数方面优于最先进的方法。

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  • 来源
    《IEEE transactions on industrial informatics》 |2020年第2期|1045-1057|共13页
  • 作者

    Du Yang; Sun Yu-E; Huang He; Huang Liusheng; Xu Hongli; Bao Yu; Guo Hansong;

  • 作者单位

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China;

    Soochow Univ Sch Rail Transportat Suzhou 215006 Peoples R China|Anhui Prov Key Lab Network & Informat Secur Wuhu 240002 Peoples R China;

    Soochow Univ Sch Comp Sci & Technol Suzhou 215006 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China;

    Univ Sci & Technol China Sch Software Engn Suzhou 215123 Peoples R China;

    Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mobile crowd sensing; probabilistic graphical model; truth discovery;

    机译：移动人群感应;概率图形模型;真相发现;

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