群智感知中用户细粒度可靠性与真值预估模型

doi:10.13190/j.jbupt.2021-217

北京邮电大学学报 ›› 2022, Vol. 45 ›› Issue (4): 70-76.doi: 10.13190/j.jbupt.2021-217

群智感知中用户细粒度可靠性与真值预估模型

刘丽坤^1,2, 邱铁^1,2, 徐天一^1,2, 陈宁^1,2, 万志国³

1. 天津大学智能与计算学部, 天津 300350;
2. 天津市先进网络技术与应用重点实验室, 天津 300350;
3. 之江实验室, 浙江 311121

收稿日期:2021-09-26 出版日期:2022-08-28 发布日期:2022-06-26
通讯作者: 邱铁(1980—),男,教授,邮箱:qiutie@ieee.org。 E-mail:qiutie@ieee.org
作者简介:刘丽坤(1996—),女,硕士生。
基金资助:
国家自然科学基金项目（U2001204）；国家重点研发计划项目（2019YFB1703600）；之江实验室开放课题（2021KF0AB02）

User Fine-Grained Reliability and Truth Estimate Model on Mobile Crowdsensing

LIU Likun^1,2, QIU Tie^1,2, XU Tianyi^1,2, CHEN Ning^1,2, WAN Zhiguo³

1. College of Intelligence and Computing, Tianjin University, Tianjin 300350, China;
2. Tianjin Key Laboratory of Advanced Networking, Tianjin 300350, China;
3. Zhijiang Laboratory, Zhejiang 311121, China

Received:2021-09-26 Online:2022-08-28 Published:2022-06-26

摘要/Abstract

摘要： 为了提高群智感知中感知数据的质量问题，提出了一种基于用户细粒度可靠性预估任务真值的方法，通过用户建模筛选出高质量数据。首先根据影响用户执行任务的瞬时因素评估用户的实时可靠性；其次，在刻画历史信誉度方面，引入信息熵衡量用户的信誉分布，包括用户总体信誉分布和在不同类别任务下的信誉分布；基于用户可靠性设计了有效的真值预估方法预估任务真值。实验结果表明，所提模型能够有效地评估用户在多类别任务下的可靠性，提高任务真值预估的准确率。

关键词: 移动群智感知, 可靠性模型, 真值预估

Abstract: To improve perceived data quality in mobile crowdsensing, a method for estimating the truth value of crowdsensing tasks based on user fine-grained reliability is proposed, whichselect high-quality data through user modeling. First, the real-time reliability of users is evaluated according to the instantaneous factors that affect their task execution. Then, information entropy is introduced to measure the user's reputation distribution, including the user's overall reputation distribution and the reputation distribution under different tasks. Next, based on user reliability, an effective truth estimation method is designed to predict task truth. Experimental results show that the proposed model can effectively evaluate the reliability of users in multi-type tasks and improve the accuracy of task truth estimation.

Key words: mobile crowdsensing, reliability model, truth estimate

中图分类号:

TP393

刘丽坤, 邱铁, 徐天一, 陈宁, 万志国. 群智感知中用户细粒度可靠性与真值预估模型[J]. 北京邮电大学学报, 2022, 45(4): 70-76.

LIU Likun, QIU Tie, XU Tianyi, CHEN Ning, WAN Zhiguo. User Fine-Grained Reliability and Truth Estimate Model on Mobile Crowdsensing[J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(4): 70-76.

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群智感知中用户细粒度可靠性与真值预估模型

User Fine-Grained Reliability and Truth Estimate Model on Mobile Crowdsensing

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