A Locality Sensitive Hashing Technique for Categorical Data

被引：4
|
作者：
Lee, Kyung Mi [1 ]
Lee, Keon Myung [1 ]
机构：
[1] Chungbuk Natl Univ, Dept Comp Sci, Chonju 361763, Chungbuk, South Korea
来源：
INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS, PTS 1-4 | 2013年 / 241-244卷
关键词：
data analysis; categorical data; locality sensitive hashing; similar pair identification;
D O I：
10.4028/www.scientific.net/AMM.241-244.3159
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The measured data may contain various types of attributes such as continuous, categorical, and set-valued attributes. Several locality-sensitive hashing techniques, which enable to find similar pairs of data in a fast and approximate way, have been developed for data with either numeric or set-valued attributes. This paper introduces a new locality sensitive-hashing technique applicable to data with categorical attributes.
引用
收藏
页码：3159 / 3164
页数：6
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