Measuring Similarity between Sequential Datasets

摘要：

　　Similarity measurement is a basic problem in data mining,but little work focuses on the similarity between sequential datasets.We propose the density-emerging pattern.And we propose a novel similarity measurement between sequential datasets based on the quality of shared-density-aware and shared-emerging patterns.Similarity measuring can be di-vided into three stages,i.e.,pattern mining,evaluating the quality of patterns,and evaluating similarity.We performed experiments on real protein sequence datasets to test the effectiveness and efficiency of our method.A case study of sequential data set classification was carried out and high accuracy was obtained.The results show that our method is able to be effectively used in the classification of sequential datasets.

关键词： Sequential Datasets Similarity Density-Aware Pattern

作者: Xiaohui Zhang Jie Zuo

作者单位: Sichuan University Chengdu,China

会议类型: 国际会议

会议名称: 2019国图灵大会(ACM Turing Celebration conference-China 2019 )

会议地点: 成都

会议语种:英文

页码: 53-57

在线出版日期: 2019-05-17（万方平台首次上网日期，不代表论文的发表时间）