Approximate indexing in road network databases

Citations

SCOPUS

4

초록

In this paper, we address approximate indexing for efficient processing of k-nearest neighbor(k-NN) queries in road network databases. Previous methods suffer from either serious performance degradation in query processing or large storage overhead because they did not employ indexing mechanisms based on their network distances. To overcome these drawbacks, we propose a novel method that builds an index on those objects in a road network by approximating their network distances and processes k-NN queries efficiently by using that index. Also, we verify the superiority of the proposed method via extensive experiments using the real-life road network databases.

키워드

Approximate indexingData structuresK-nearest neighbor queriesRoad network databasesIndexing mechanismsK-nearest neighborsK-nearest-neighbor queriesK-NN queryNetwork distanceNovel methodsPerformance degradationRoad networkStorage overheadComputer scienceData structuresDatabase systemsIndexing (materials working)Indexing (of information)Roads and streetsMotor transportation
제목
Approximate indexing in road network databases
저자
Lee, Sang-ChulKim, Sang-WookLee, JunghoonYoo, Jae Soo
DOI
10.1145/1529282.1529632
발행일
2009-03
유형
Conference Paper
저널명
Proceedings of the ACM Symposium on Applied Computing
페이지
1568 ~ 1572