Improving the Nearest Neighbor Search Algorithm for Asymmetric Distance Functions

Student: Ershov Andrey

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2019

In this project the existing methods for solving the problem of finding the nearest neighbor (k nearest neighbors), their advantages and disadvantages were described. However, these methods are not well studied when working with asymmetric distance functions and our main task was to study and improve existing methods to solve this problem, as well as their adaptation to use with asymmetric functions of distance. Also within the framework of this work, the existing algorithms implemented in the open source library NMSLIB were modified. A series of tests was conducted to analyze the improved performance, graphs were built with the results and a number of points and hypotheses were put forward for further research.

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