Singular value decomposition 기반 고차원 인덱스 구조

• 영문명: A High-Dimensional Index Structure Based on Singular Value Decomposition
• 발행기관: 강원대학교 산업기술연구소
• 저자명: 김상욱(Kim Sang Wook) Charu Aggarwal Philip S. Yu
• 간행물 정보: 『산업기술연구』vol.20, 1~6쪽, 전체 6쪽
• 주제분류: 공학 > 공학일반
• 파일형태: PDF
• 발행일자: 2000.09.30

영문 초록

The nearest neighbor query is an important operation widely used in multimedia databases for finding the object that is most similar to a given query object. Most of techniques for processing nearest neighbor queries employ multidimensional indexes for effective indexing of objects. However, the performance of previous multidimensional indexes, which use N-dimensional rectangles or spheres for representing the capsule of the object cluster, deteriorates seriously as the number of dimensions gets higher. This problem and the query processing method using it. We also verify the superiority of our approach through performance evaluation by performing extensive experiments.

목차

Abstract

I. 서론

II. 연구 동기

III. 제안하는 기법

IV. 성능 평가

V. 결론

참고문헌

키워드

multimedia databases nearest neighbor queries high dimensional indexing