Efficiently Processing Spatial and Keyword Queries in Indoor Venues

Due to the growing popularity of indoor location-based services, data management has received significant research attention in past few years. However, we observe that existing indexing and query processing techniques for space do not fully exploit properties space. Consequently, they provide below par performance which makes them unsuitable large venues with high workloads. In this paper, first propose two novel indexes called Indoor Partitioning Tree (IP-Tree) Vivid IP-Tree (VIP-Tree) are carefully designed by utilizing venues. The proposed lightweight, have small pre-processing cost near-optimal shortest distance path queries. We also study spatial keyword queries a structure Keyword (KP-Tree) objects an partition. efficient algorithm based on VIP-Tree KP-Trees efficiently answer Our extensive experimental real synthetic sets demonstrates our outperform solutions several orders magnitude.