一种面向任务需求的群智感知任务分配模型  

A task assignment model of mobile crowd sensing oriented requirements

作　　者：王鑫 廖祎玮[1] 赵国生[1] 王健[2] 谢宝文 WANG Xin;LIAO Yi-wei;ZHAO Guo-sheng;WANG Jian;XIE Bao-wen(School of Computer Science and Information Engineering,Harbin Normal University,Harbin 150025;School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,China)

机构地区：[1]哈尔滨师范大学计算机科学与信息工程学院,黑龙江哈尔滨150025 [2]哈尔滨理工大学计算机科学与技术学院,黑龙江哈尔滨150080

出　　处：《计算机工程与科学》2021年第8期1512-1520,共9页Computer Engineering & Science

基　　金：国家自然科学基金(61202458,61403109);黑龙江省自然科学基金(F2017021);哈尔滨市科技创新人才研究专项资金(2016RAQXJ036)。

摘　　要：针对群智感知平台中的任务分配问题,提出了一种任务需求特征提取算法和用户标签分类方法相结合的TREAULCM任务分配模型。首先,通过任务需求特征提取算法提取感知任务的类别关键词;然后,通过多线性神经网络和多核学习对数据集进行训练得到分类器,通过分类器对用户的类型标签进行预测;最后,根据任务的类别关键词结合空间位置信息和用户参与度筛选有该任务类别标签且最大化满足任务需求的用户分发任务。仿真结果表明,TREAULCM任务分配模型在任务匹配度和任务分配效率方面有较好的可行性。Aiming at the task assignment issue in the mobile crowd sensing platform,a task assignment model combining task demand feature extraction algorithm with user label classification method is proposed.Firstly,the task demand feature extraction algorithm is used to extract the category keywords of sensing tasks.Then,the data set is trained by multi-linear neural network and multi-kernel learning to get the classifier,and the user’s type labels are predicted by the classifier.Finally,according to the category keywords of the tasks,combined with the spatial location information and user participation,the users who have the task category labels and meet the task requirements are selected to distribute tasks.Simulation results show that the proposed model has good feasibility in terms of task matching and task assignment efficiency.

关 键 词：移动群智感知 特征提取 用户标签 多线性神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]