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http://dx.doi.org/10.6109/jkiice.2010.14.4.875

A Study on the CBR Pattern using Similarity and the Euclidean Calculation Pattern  

Yun, Jong-Chan (부경대학교 병렬운영체제 및 데이터마이닝연구실)
Kim, Hak-Chul (부경대학교 전자공학과)
Kim, Jong-Jin (부경대학교 전자공학과)
Youn, Sung-Dae (부경대학교 컴퓨터공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.14, no.4, 2010 , pp. 875-885 More about this Journal
Abstract
CBR (Case-Based Reasoning) is a technique to infer the relationships between existing data and case data, and the method to calculate similarity and Euclidean distance is mostly frequently being used. However, since those methods compare all the existing and case data, it also has a demerit that it takes much time for data search and filtering. Therefore, to solve this problem, various researches have been conducted. This paper suggests the method of SE(Speed Euclidean-distance) calculation that utilizes the patterns discovered in the existing process of computing similarity and Euclidean distance. Because SE calculation applies the patterns and weight found during inputting new cases and enables fast data extraction and short operation time, it can enhance computing speed for temporal or spatial restrictions and eliminate unnecessary computing operation. Through this experiment, it has been found that the proposed method improves performance in various computer environments or processing rate more efficiently than the existing method that extracts data using similarity or Euclidean method does.
Keywords
Case-Based Reasoning; Similarity; Euclidean; Data Mining;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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