Multi-ant colonies synchronization optimization based multi-truth discovery algorithm

Feng Qin1
Cao Jianjun2
Zheng Qibin1
Zhang Lei1
Weng Nianfeng2
Li Hongmei1
1. Command & Control Engineering College, Army Engineering University of PLA, Nanjing 210007, China
2. The 63rd Research Institute, National University of Defense Technology, Nanjing 210007, China

Abstract

In order to improve the accuracy of truth discovery in multi-truth scene, this paper proposed a multi-ant colonies synchronization optimization based multi-truth discovery(MAC-SO-MTD) algorithm. It modeled the multi-truth discovery problem as the subset problem, which goal was maximizing the weighted sum of similarity between the set of observations provided by each data source and the set of true values of the object. On this basis, then it designed ant colony algorithm to solve the problem. It set ant colonies according to the number of objects. Based on the subset problem's structure graph, this paper used routes' probability transition equations to search for truths synchronically. After one cycle, the best route of this cycle updating and no updating were two instances of updating pheromone, which improved the convergence speed. Finally, the analysis of algorithm complexity and contrast experiment on the real data set validates the superiority of the algorithm.

Foundation Support

国家自然科学基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.05.0453
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 1
Section: Algorithm Research & Explore
Pages: 44-49
Serial Number: 1001-3695(2020)01-009-0044-06

Publish History

[2020-01-05] Printed Article

Cite This Article

冯钦, 曹建军, 郑奇斌, 等. 基于多蚁群同步优化的多真值发现算法 [J]. 计算机应用研究, 2020, 37 (1): 44-49. (Feng Qin, Cao Jianjun, Zheng Qibin, et al. Multi-ant colonies synchronization optimization based multi-truth discovery algorithm [J]. Application Research of Computers, 2020, 37 (1): 44-49. )

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