A filtering method for k-nearest neighbor query processing in multimedia data retrieval applications

Efficient query processing in multi-dimensional indexing structures is an important issue for effective employment of multimedia data applications. A considerable number of studies, to date, have been conducted in this area. However the efficiency of the proposed solutions generally deteriorates as...

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Bibliographic Details
Main Authors: Byung-Gon Kim, Jae-Ho Lee, Noh, S.H., Hae-Chull Lim
Format: Conference Proceeding
Language:English
Subjects:
Application software
Computer science education
Data engineering
Electronic mail
Filtering
Filters
Indexing
Information retrieval
Nearest neighbor searches
Query processing
Online Access:Request full text
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Summary:Efficient query processing in multi-dimensional indexing structures is an important issue for effective employment of multimedia data applications. A considerable number of studies, to date, have been conducted in this area. However the efficiency of the proposed solutions generally deteriorates as the dimension of the data increases. We introduce a filtering method for efficient processing of k-nearest neighbor queries in multi-dimensional indexing structures. The proposed method is based on the R*-tree, and uses a vantage point for effective similarity searches. Through the use of a vantage point we are abler to filter out data objects and decrease the distance computation time. Experimental results show that the k-nearest neighbor search that uses the proposed method consistently outperforms the search performance that uses the existing method for the R*-tree.
DOI:10.1109/TENCON.1999.818419