Geometric approaches for top-k queries

Abstract

Top- k processing is a well-studied problem with numerous applications that is becoming increasingly relevant with the growing availability of recommendation systems and decision making software. The objective of this tutorial is twofold. First, we will delve into the geometric aspects of top- k processing. Second, we will cover complementary features to top- k queries, with strong practical relevance and important applications, that have a computational geometric nature. The tutorial will close with insights in the effect of dimensionality on the meaningfulness of top- k queries, and interesting similarities to nearest neighbor search.