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 language | English |
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Title of host publication | Lecture Notes in Electrical Engineering |
Publisher | Springer Verlag |
Pages | 797-803 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 2015 |
Publication series
Name | Lecture Notes in Electrical Engineering |
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Volume | 373 |
ISSN (Print) | 1876-1100 |
ISSN (Electronic) | 1876-1119 |
Bibliographical note
Publisher Copyright:© Springer Science+Business Media Singapore 2015.
Keywords
- K-nearest neighbor query
- Nearest user-specified group query
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering