HCTree+: A workload-guided index for approximate [formula omitted]NN search

Abstract

The problem of approximate k-nearest neighbor search in high-dimensional space is a fundamental problem in many applications. We have observed that most existing approaches are unable to leverage the query results to improve the search performance. To address this limitation, we present a new index, called HCTree+, that aims to improve the query performance based on incoming queries and their results. First, we adopt a simple yet effective index to support efficient search. Second, incoming queries and their results are used to optimize the index dynamically for future queries. The experimental study shows that HCTree+ outperforms the state-of-the-art algorithms in terms of accuracy while achieving the desired efficiency.