Specifications
Controlled terms: Jet pumps - Research - Water management
Uncontrolled terms: Artificial density-flow - Its efficiencies - Present situation -
Pulsed jets - Self excited oscillation - Study and applications - Water conservancy
Classification code: 444 Water Resources - 446 Waterworks - 618.2 Pumps - 631.1
Fluid Flow, General - 901.3 Engineering Research
DOI: 10.4028/www.scientific.net/AMM.341-342.506
Database: Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.
7.
Accession number: 20133516678779
Title: Mining frequent trajectory using FP-tree in GPS data
Authors: Li, Junhuai1 ; Wang, Jinqin1 ; Liu, Hailing2 ; Yu, Lei1 ; Zhang, Jing1/李军怀;;于蕾;张璟
Author affiliation: 1 School of Computer Science and Engineering, Xi'an University of
Technology, Xi'an 710048, China
2 College of Electronic Information Engineering, Chongqing University of Science and
Technology, Chongqing 400050, China
Corresponding author: Li, J. (lijunhuai@xaut.edu.cn)
Source title: Journal of Computational Information Systems
Abbreviated source title: J. Comput. Inf. Syst.
Volume: 9
Issue: 16
Issue date: August 15, 2013
Publication year: 2013
Pages: 6555-6562
Language: English
ISSN: 15539105
Document type: Journal article (JA)
Publisher: Binary Information Press, P.O. Box 162, Bethel, CT 06801-0162, United States
Abstract: Pervasiveness of location-acquisition technologies makes it convenient to collect the
movement data of moving objects, and the spatial-temporal information contained implicitly in
the historical trajectories unveils important knowledge about movement behaviors. This paper
presents a novel frequent trajectory mining method using FP-Tree Most existing approaches
transform trajectories into sequences of popular region-ids using a statically predefined grid of
cells with the same size, and then merge popular cells into larger popular regions. However, due
to the size of these popular regions have not been limited, the movements of objects in the
region may be lost. And predefined grid may be lack of adaptability. This study defines a
Boundary Function to limit the maximum size of the popular regions and selects the size of the
grid dynamically by defining a distance threshold d. Then, an improved FP-Tree algorithm is
proposed to mine frequent trajectories. The experimental results show our method is efficient. ©
2013 Binary Information Press.
Number of references: 8
Main heading: Trees (mathematics)
Controlled terms: Forestry - Global positioning system - Mining - Trajectories