《计算机应用研究》|Application Research of Computers

基于多蚁群同步优化的多真值发现算法

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

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作者 冯钦,曹建军,郑奇斌,张磊,翁年凤,李红梅
机构 1.陆军工程大学 指挥控制工程学院,南京 210007;2.国防科技大学 第六十三研究所,南京 210007
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文章编号 1001-3695(2020)01-009-0044-06
DOI 10.19734/j.issn.1001-3695.2018.05.0453
摘要 为提高在多真值场景下真值发现的准确性,提出一种多蚁群同步优化的多真值发现算法(multi-ant co-lonies synchronization optimization based multi-truth discovery algorithm,MAC-SO-MTD)。以最大化各数据源提供的观测值集合与该对象真值集合之间相似度的加权和为目标,将多真值发现问题建模为求解子集问题。在此基础上设计蚁群算法进行求解:根据对象个数设置相应的蚁群,构造子集问题的有向图,利用路径概率转移公式进行同步搜索真值;将信息素更新分为本次迭代最优更新和本次迭代不更新,提高了算法的收敛速度。最后,通过算法复杂度分析和在真实数据集上的实验验证了该算法的优越性。
关键词 数据清洗; 数据冲突; 多真值发现; 子集问题; 蚁群优化
基金项目 国家自然科学基金资助项目
本文URL http://www.arocmag.com/article/01-2020-01-009.html
英文标题 Multi-ant colonies synchronization optimization based multi-truth discovery algorithm
作者英文名 Feng Qin, Cao Jianjun, Zheng Qibin, Zhang Lei, Weng Nianfeng, Li Hongmei
机构英文名 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
英文摘要 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.
英文关键词 data cleaning; data conflict; multi-truth discovery; subset problem; ant colony optimization
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收稿日期 2018/5/21
修回日期 2018/7/13
页码 44-49
中图分类号 TP311
文献标志码 A