Inverted-file R-tree Index Nodes Clustering Based on Multi-objective Optimization

The evolutionary multi-objective optimization algorithm was used to optimize the clustering and splitting of nodes in the construction of inverted spatial objects index tree(ITSR) in this paper. Considering the objective factors including object's coverage, overlap, group center distance, directory rectangle perimeter and the word similarity between tree nodes, etc., a multi-objective optimization model for solving the optimal ITSR construction is established. To solve the model, this paper find a novel method of constructing high efficiency inverted text-spatial R-tree index. The experimental results show that the algorithm supports the multi-objective optimal clustering of ITSR with high efficiency and accuracy .