차원 축소 벡터들을 위한 인덱싱 및 검색

Indexing and Searching for Reduced-Dimensional Vectors

초록

In this paper, we first address the problems associated with indexing and searching for reduced-dimensional vectors, which are reduced by using a combination of angle approximation and dimension grouping. Then, we propose a novel method to solve the problems. We also show the superiority of the proposed method by performing extensive experiments with synthetic and real-life data sets.

키워드

Multimedia Information RetrievalMulti-dimensional IndexingQuery ProcessingDimensionality ReductionMultimedia Information RetrievalMulti-dimensional IndexingQuery ProcessingDimensionality Reduction멀티미디어 정보검색다차원 색인질의 처리차원 축소
제목
차원 축소 벡터들을 위한 인덱싱 및 검색
제목 (타언어)
Indexing and Searching for Reduced-Dimensional Vectors
저자
정승도김상욱최병욱
발행일
2010-02
저널명
정보과학회논문지 : 데이타베이스
37
1
페이지
44 ~ 49