상세정보
학술지
α-Probabilistic Flexible Aggregate Nearest Neighbor Search in Road Networks using Landmark Multidimensional Scaling
- 저자
- 정문영, 노웅기
- 발행일
- 202102
- 출처
- Journal of Supercomputing, v.77 no.2, pp.2138-2153
- ISSN
- 0920-8542
- 출판사
- Springer
- 협약과제
- 20HS5800, 클라우드 엣지 기반 도시교통 브레인 핵심기술 개발, 정문영
- 초록
- In spatial database and road network applications, the search for the nearest neighbor (NN) from a given query object q is the most fundamental and important problem. Aggregate nearest neighbor (ANN) search is an extension of the NN search with a set of query objects Q= { q, ?떙 , qM-1} and finds the object p?닓 that minimizes g{ d(p?닓, qi) , qi?늿 Q} , where g (max or sum) is an aggregate function and d() is a distance function between two objects. Flexible aggregate nearest neighbor (FANN) search is an extension of the ANN search with the introduction of a flexibility factor ??(0
- KSP 제안 키워드
- ANN search, Aggregate function, Aggregate nearest neighbor, Comparison experiment, Distance-based, Euclidean space, Higher performance, Multi-dimensional scaling(MDS), Network applications, Network objects, Performance comparison