11 Applications of Nearest Neighbors Search
This chapter covers
- Designing a solution for the “closest hub” problem using NN search
- Adding filtering to NN search to support business logic and dynamic supply
- Dealing with faulty networks and failure, and deploying to the real world
- Applying NN search to other domain like physics and computer graphics
- Introducing clustering
It’s time to harvest what we seeded, and to start solving the problems we have described in the last few chapters. As always, after a deep dive in theory, we try to give you a “real-life” angle, and in this chapter, we will incrementally build a solution for the “closest hub” problem, one that keeps into account many of the issues a real application would face. But do not be mistaken: we can’t tackle all the possible issues here, and this doesn’t aim to be an exhaustive description of all the possible problems you would face, neither it is a runbook about how to operate your e-commerce application: only practice, rolling up your sleeves and getting burned while trying, can teach you that. What you can find in this chapter, besides a few examples of real-world technical challenges, is a hands-on example of the analysis process that brings you from a solution “on paper” for your use case, to a working application coping with the complex facets of reality.