Systems Engineering and Electronics

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Truth finder algorithm based on entity attributes for data conflict solution

Xiaolong Xu1,2,*, Xinxin Liu1, Xiaoxiao Liu3, and Yanfei Sun4   

  1. 1. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
    2. State Key Laboratory of Information Security, Chinese Academy of Sciences, Beijing 100093, China;
    3. Institute of Big Data Research at Yancheng, Nanjing University of Posts and Telecommunications, Yancheng 224005, China;
    4. Science and Technology Department, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Online:2017-06-20 Published:2010-01-03

Abstract:

The Internet now is a large-scale platform with big data. Finding truth from a huge dataset has attracted extensive attention, which can maintain the quality of data collected by users and provide users with accurate and efficient data. However, current truth finder algorithms are unsatisfying, because of their low accuracy and complication. This paper proposes a truth finder algorithm based on entity attributes (TFAEA). Based on the iterative computation of source reliability and fact accuracy, TFAEA considers the interactive degree among facts and the degree of dependence among sources, to simplify the typical truth finder algorithms. In order to improve the accuracy of them, TFAEA combines the oneway text similarity and the factual conflict to calculate the mutual support degree among facts. Furthermore, TFAEA utilizes the symmetric saturation of data sources to calculate the degree of dependence among sources. The experimental results show that TFAEA is not only more stable, but also more accurate than the typical truth finder algorithms.