HCTree+: A workload-guided index for approximate kNN search

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,...

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Bibliographic Details
Published inInformation sciences Vol. 581; pp. 876 - 890
Main Authors Li, Lingli, Xu, Jie, Li, Yu, Cai, Jingwen
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.12.2021
Subjects
[formula omitted]NN
Index
Nearest neighbor search
Nearest neighbor search
kNN
Index
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Summary: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.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2021.10.027