Projected Nearest Neighbor Problem

Speaker: David CHENG

Abstract

K-nearest neighbor (k-NN) problem has many applications, such as in multimedia search, fraud detection and information retrieval. However, most current solutions on this problem perform poorly when the dimension of the dataset is high. In my presentation, I would first discuss the issues of the k-NN problem in high dimensional space. Then I would introduce a very similar problem called projected k-NN problem. I would also study some previous method on this problem as well as presenting our proposed method. Our method would be mainly based on the data structure called B+-Tree.