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NearTree, a data structure and a software toolkit for the nearest-neighbor problem.

Lawrence C Andrews¹, Herbert J Bernstein²

¹9515 NE 137th Street, Kirkland, WA 98034, USA.

Journal of Applied Crystallography

|June 9, 2016

Summary

The neartree data structure efficiently organizes metric data for nearest-neighbor problems in fields like crystallography. This software tool constructs neartrees, offering near-optimal performance and various query functionalities.

Keywords:

nearest-neighbor search neartree data structure post office problem

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Area of Science:

Computational science
Data structures
Crystallography

Background:

Nearest-neighbor problems are common in various scientific fields, including crystallography.
Existing data structures may not always offer optimal performance for metric data retrieval.

Purpose of the Study:

To introduce the neartree data structure for organizing and retrieving metric data.
To present NearTree, a software tool for constructing neartrees and performing queries.

Main Methods:

Development of the neartree data structure.
Implementation of the NearTree software tool.
Evaluation of neartree performance for nearest-neighbor problems.

Main Results:

The neartree data structure offers a flexible approach to metric data organization.
NearTree software facilitates the construction of neartrees.
Neartrees can achieve near-optimal performance in specific nearest-neighbor problem scenarios.

Conclusions:

The neartree data structure is a valuable tool for addressing nearest-neighbor problems.
The NearTree software provides practical utility for researchers working with metric data.