Multidimensional Data Mining Based on Tensor

被引:1
|
作者
Yokobayashi, Ryohei [1 ]
Miura, Takao [1 ]
机构
[1] Hosei Univ, Dept Adv Sci, Kajinocho 3-7-2, Koganei, Tokyo 1868584, Japan
关键词
Multidimensional Association Rules; Data Mining; Tensor; Data Model;
D O I
10.1109/ICDMW.2018.00164
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a data manipulation method to extract multidimensional association rules in the framework of Tensor Data Model (TDM). By using the TDM, high order data structure and naive description for information retrieval are possible. Among others, we discuss multidimensional association rule mining here. Usually, association rule mining (or extraction of association rules) concerns about co-related transaction records of single predicate, and hard to examine the ones over multiple predicates since it takes heavy time- and space-complexities. Here, several operations specific to multidimensional data mining to reduce amount of description can be modeled by using TDM.
引用
收藏
页码:1144 / 1151
页数:8
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