Efficiently navigate spatial data with this comparative study. This paper compares two methods for distance browsing in spatial databases using R-trees: the conventional k-nearest neighbor algorithm and an incremental approach. The incremental nearest neighbor algorithm was found to significantly outperforms the former for distance browsing queries. By being able to obtain k + 1 nearest neighbors without calculating k + 1 nearest neighbors from scratch is useful when processing complex queries where one of the conditions involves spatial proximity. The study shows that the incremental nearest neighbor algorithm is optimal regarding the spatial data structure. This leads to efficiency in complex queries where spatial proximity is a key factor.
This paper aligns with the ACM Transactions on Database Systems' focus on database systems and spatial data structures. The study's comparative analysis of nearest neighbor algorithms contributes to the journal's discussions on optimizing spatial data retrieval and improving database performance. By presenting a general incremental nearest neighbor algorithm, the paper offers a valuable tool for database professionals.