Multidimensional datasets are getting more extensively used in Geographic Information Systems (GIS) applications in recent years. Due to large volume of these datasets efficient querying becomes a significant problem. For this purpose, before creating index structure with these enormous datasets, choosing an efficient index structure is an urgent necessity. The aim of this thesis is to develop an efficient, flexible and extendible index structure which comprises 3D spatial data in primary index and fuzzy attributes in secondary index. These primary and secondary indexes are handled in a coupled structure. Firstly, a 3D spatial primary index is built by using X-tree structure, and then a fuzzy secondary index is overlaid over the X-tree structure. The coupled structure is shown more efficient on a certain class of queries than uncoupled index structures comprising 3D spatial data in primary index and fuzzy attributes in secondary index separately. In uncoupled index structure, we provided 3D spatial primary index by using X-tree index structure and fuzzy secondary index by using BPlusTree index structure.

This thesis summarizes the information retrieval theory, the relational model basic and focuses on the data indexing in relational database systems. The thesis focuses on multimedia data searching. It includes description of automatic multimedia data content extraction and multimedia data indexing. Practical part discusses design and solution implementation for improving query effectivity for multidimensional vector similarity which describes multimedia data. Thesis final part discusses experiments with this solution.