徐秀娟

个人信息Personal Information

副教授

博士生导师

硕士生导师

性别:女

毕业院校:吉林大学

学位:博士

所在单位:软件学院、国际信息与软件学院

学科:软件工程

办公地点:开发区综合楼

电子邮箱:xjxu@dlut.edu.cn

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论文成果

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Deviation Methods via Social Review Graph In Evaluation Systems of Online Store

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论文类型:会议论文

发表时间:2014-05-22

收录刊物:EI、CPCI-S、Scopus

卷号:2015-October

页面范围:229-232

关键字:deviation; evalution; social network mining

摘要:Evaluation system is an important issue in data mining. In evaluation system, all reviewers try to assign fair scores on a set of object. We want to obtain fair reviewers for all objects. However, it is the real fact that reviewer may deviate in their score assigned to the same object. Therefore, the deviation is unavoidable in evaluation systems. In this paper we define deviation of evaluation systems. Then, two novel methods are constructed to measure deviation: deviation from Correct-Coreviewers and deviation from MaxGap -Coreviewers. The experimental results show that the proposed measure methods are efficient and can be used to solve deviation problem in evaluation systems effectively.