Top K Nearest Book Searching Approach in Metaverse Libraries Based on R-Tree

With the rapid development of network information technology, more and more researchers focus on the construction of metaverse libraries. What remains a challenge is how to find the nearest books in the metaverse libraries accurately and effectively. This paper proposes a top
$k$
nearest book searching approach in metaverse libraries based on R-tree. We compare the proposed searching algorithm based on R-tree with the baseline linear scanning in a 2D graph. The state-of-the-art searching algorithm based on grids is also compared. Experimental results demonstrate that our proposed searching algorithms based on R-tree outperform linear scanning and the best searching algorithm based on grids by being approximately 99.940% faster and approximately 90.998% faster respectively. Furthermore, the proposed approach, the searching algorithm based on R-tree, can be extended to find the top
$k$
nearest points of q (x, y, z) in 3D spaces in metaverse libraries if the bookshelves are designed to be 3D ones.