Nearest Neighbour (NN) is one of the important queries and analyses for spatial application. In normal practice, spatialaccessmethod structure is usedduring the Nearest Neighbour query execution to retrieve informa...
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Nearest Neighbour (NN) is one of the important queries and analyses for spatial application. In normal practice, spatialaccessmethod structure is usedduring the Nearest Neighbour query execution to retrieve information from the database. However, most of the spatialaccessmethod structures are still facing with unresolved issues such as overlapping among nodes and repetitive data entry. This situation will perform an excessive Input/Output (IO) operation which is inefficient for data retrieval. The situation will become more crucial while dealing with 3ddata. The size of 3ddata is usually large due to its detail geometry and other attached information. In this research, a clustered3d hierarchical structure is introduced as a 3d spatial access method structure. The structure is expected to improve the retrieval of Nearest Neighbour information for 3d objects. Several tests are performed in answering Single Nearest Neighbour search and k Nearest Neighbour (kNN) search. The tests indicate that clustered hierarchical structure is efficient in handling Nearest Neighbour query compared to its competitor. From the results, clustered hierarchical structure reduced the repetitive data entry and the accessed page. The proposed structure also produced minimal Input/Output operation. The query response time is also outperformed compared to the other competitor. For future outlook of this research several possible applications are discussed and summarized.
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