Which type of problem is specifically addressed by Nearest Neighbor Search in Oracle AI?

Nearest Neighbor Search in Oracle AI is specifically designed to address similarity search problems. This technique involves finding the data points that are closest to a given query point in a multi-dimensional space. It operates on the principle that similar objects are located in proximity to each other based on certain criteria.

In applications such as recommendation systems, image recognition, and natural language processing, identifying similar items helps in making predictions or suggestions based on user behavior or input data. By utilizing mathematical algorithms and data structures, Nearest Neighbor Search efficiently determines the nearest points, which is critical in various AI and machine learning tasks.

Other types of problems, such as linear regression and encryption issues, do not align with the core capabilities of Nearest Neighbor Search. Linear regression involves modeling the relationship between dependent and independent variables, which requires a different analytical approach. Meanwhile, data encryption focuses on securing data through cryptographic methods, which is unrelated to the concept of searching for similar items or points within a dataset. Therefore, similarity search problems are distinctly addressed by Nearest Neighbor Search, making it the correct answer.