We present a new approach for the approximate K-nearest neighbor search based on
navigable small world graphs with controllable hierarchy (Hierarchical NSW, HNSW). The …

The in-memory algorithms for approximate nearest neighbor search (ANNS) have achieved
great success for fast high-recall search, but are extremely expensive when handling very …

The KNN algorithm is one of the most popular data mining algorithms. It has been widely
and successfully applied to data analysis applications across a variety of research topics in …

This review considers the class of index structures for fast similarity search. In constructing
and applying such structures, only information on values or ranks of some …

Various problems are just rising with regard to mining in massive datasets, among which
finding similar documents can be pinpointed. The Shingling method converts this problem to …

通过在3 种不同间伐强度的华北落叶松人工林作业区设置样地, 利用Hegyi 简单竞争指数模型对
不同树种对象木以及经营核心目标树的竞争压力量化表达比较, 并对抚育间伐对林分竞争特征的 …

This manuscript presents the extreme pivots (EP) metric index, a data structure, to speed up
exact proximity searching in the metric space model. For the EP, we designed an automatic …

Consultas por similaridade constituem um paradigma base para o tratamento de dados que
só possuem uma relação de distância entre si. Esse paradigma suporta diversas tarefas …

The purpose of this qualitative case study was to explore the usefulness of higher-level
search techniques to reduce students' cognitive load. The central question of the study …

Рассмотрен класс таких индексных структур для быстрого поиска по сходству, при
конструировании и применении которых используется только информация о значениях …