Ordered matrix representation supporting the visual analysis of associated data

作     者：Yi CHEN Cheng LV Yue LI Wei CHEN Kwan-Liu MA Yi CHEN;Cheng LV;Yue LI;Wei CHEN;Kwan-Liu MA

作者机构：Beijing Key Laboratory of Big Data Technology for Food SafetyBeijing Technology and Business University State Key Laboratory of CAD&CGZhejiang University Department of Computer ScienceUniversity of California 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2020年第63卷第8期

页      面：236-238页

核心收录：

学科分类：0810[工学-信息与通信工程] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Key R&D Program of China (Grant No. 2018YFC1603602) National Natural Science Foundation of China (Grant Nos. 61972010, 61772456, 61761136020) Basic Research Project of the Ministry of Science and Technology (Grant No. 2015FY111200) 

主　　题：Visualization RW-Rank Ordered Matrix Associated Data Pesticide Residue Data 

摘      要：Associated data, which refer to sets of entities with specific relations and relational weights that can usually be expressed in a relational matrix, are found in many fields. Two typical examples are the pesticide residue dataset in food-safety, in which pesticides are associated with agricultural products [1], and E-transaction dataset, in which there is special relation between buyer and seller [2].However, on large data scales, finding the key en-