Approximate Nearest Neighbor Searching in Multimedia Databases

In this paper, we develop a general framework for approximate nearest neighbor queries. We categorize the current approaches for nearest neighbor query processing based on either their ability to reduce the data set that needs to be examined, or their ability to reduce the representation size of each data object. We first propose modifications to wellknown techniques to support the progressive processing of approximate nearest neighbor queries. A user may therefore stop the retrieval process once enough information has been returned. We then develop a new technique based on clustering that merges the benefits of the two general classes of approaches. Our cluster-based approach allows a user to progressively explore the approximate results with increasing accuracy. We propose a new metric for evaluation of approximate nearest neighbor searching techniques. Using both the proposed and the traditional metrics, we analyze and compare several techniques with a detailed performance evaluati...

• Type: Conference
• Year: 2001
• Where: ICDE
• Authors: Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agrawal, Amr El Abbadi
• Keywords: Approximate Nearest Neighbor, Database, ICDE 2001, Nearest Neighbor Queries, Nearest Neighbor Query