Abstract:

Using semantic classification for space resources index construction for the Internet of Things makes the traditional IR tree with semantic features and supports semantic query for spatial resources. A top-k semantics query optimization algorithm is proposed, and the validity of the index structure and the correctness of the results is obtained through the use of real dataset and experimental analysis. To assess the performance of the algorithm, three aspects of the construction time of the index, the query time and the query accuracy are compared. The results show that the algorithm supports semantic space resources index construction and has high query performance and accuracy.