《計算機應用研究》|Application Research of Computers

基于多蟻群同步優化的多真值發現算法

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

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作者 馮欽,曹建軍,鄭奇斌,張磊,翁年鳳,李紅梅
機構 1.陸軍工程大學 指揮控制工程學院,南京 210007;2.國防科技大學 第六十三研究所,南京 210007
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文章編號 1001-3695(2020)01-009-0044-06
DOI 10.19734/j.issn.1001-3695.2018.05.0453
摘要 為提高在多真值場景下真值發現的準確性,提出一種多蟻群同步優化的多真值發現算法(multi-ant co-lonies synchronization optimization based multi-truth discovery algorithm,MAC-SO-MTD)。以最大化各數據源提供的觀測值集合與該對象真值集合之間相似度的加權和為目標,將多真值發現問題建模為求解子集問題。在此基礎上設計蟻群算法進行求解:根據對象個數設置相應的蟻群,構造子集問題的有向圖,利用路徑概率轉移公式進行同步搜索真值;將信息素更新分為本次迭代最優更新和本次迭代不更新,提高了算法的收斂速度。最后,通過算法復雜度分析和在真實數據集上的實驗驗證了該算法的優越性。
關鍵詞 數據清洗; 數據沖突; 多真值發現; 子集問題; 蟻群優化
基金項目 國家自然科學基金資助項目
本文URL http://www.048285.live/article/01-2020-01-009.html
英文標題 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
機構英文名 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.
英文關鍵詞 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
頁碼 44-49
中圖分類號 TP311
文獻標志碼 A
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