In-memory processing for nearest user-specified group search

Hong Jun Jang, Woo Sung Choi, Kyeong Seok Hyun, Taehyung Lim, Soon Young Jung, Jaehwa Chung

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

This paper presents a nearest user-specified group (NUG) search which called a clustered NN problem. Given a set of data points P and a query point q, NUG search finds the nearest subset c ⊂ P (|c| ≥ k) from q (called user-specified group) that satisfies given conditions. Motivated by the brute-force approach for NUG search requires O (|P|2) computational cost, we propose a faster algorithm to handle NUG problem with in-memory processing. We first define clustered objects above k as a user-specified group and the NUG search problem. Moreover, the proposed solution converts a NUG search problem to a graph formulation problem, and reduces processing cost with geometric-based heuristics. Our experimental results show that the efficiency and effectiveness of our proposed approach outperforms the conventional one.

Original languageEnglish
Title of host publicationLecture Notes in Electrical Engineering
PublisherSpringer Verlag
Pages797-803
Number of pages7
DOIs
Publication statusPublished - 2015

Publication series

NameLecture Notes in Electrical Engineering
Volume373
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Keywords

  • K-nearest neighbor query
  • Nearest user-specified group query

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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