A Method to Discover Truth with Two Source Quality Metrics

摘要：

　　In many web integration applications, there are usually some sources that depict the same entity object with different descriptions, which leads to lots of conflicts.Resolving conflicts and finding the truth can be used to improve the quality of integration or to build a high-quality knowledge base, etc.In the single-truth data conflicting scenario, existing methods have limitations to distinguish false negative, also named as data missing, and false positive.So their source quality measurements are inadequate.Therefore,in this paper, we use recall and false positive rate to measure source quality and present a method to discover truth.The experimental results on three real-word data sets show that the proposed algorithm can effectively distinguish the data missing and false positive and improve the precision of truth discovery.

关键词： truth discovery data conflicts data integration single-truth scenario

作者: Dong Yu Derong Shen Mingdong Zhu Tiezheng Nie Yue Kou Ge Yu

作者单位: College of Information Science and Engineering Northeastern University Shenyang, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 161-164

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）