自行车共享网络的骨架网络提取与分析

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Data Warehousing and Mining Pub Date : 2020-07-01 DOI:10.4018/ijdwm.2020070108

Kanokwan Malang, Shuliang Wang, Yuanyuan Lv, Aniwat Phaphuangwittayakul

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引用次数: 3

摘要

Skeletonnetworkextractionhasbeenadoptedunevenlyintransportationnetworkswhosenodes它们总是被表示为空间单位。在这篇文章中，thetpks骷髅网络提取methodisproposedandappliedtobicyclesharingnetworks。Themethodaimstoreducethe networksizewhilepreservingkeytopologiesandspatialfeatures。Theauthorsquantifiedthe importanceofnodesbyanimprovedtopologypotentialalgorithm。Thespatialclusteringallows todetecthightrafficconcentrationsandallocate thenodesofeachclusteraccordingto their > spatialdistribution。Then，theskeletonnetworkisconstructedbyaggregatingthemostimportant indicatedskeletonnodes。Theauthorsexaminetheskeletonnetworkcharacteristicsanddifferent spatialinformationusingtheoriginalnetworksasabenchmark。Theresultsshowthattheskeleton networkscanpreservethetopologicalandspatialinformationsimilartotheoriginalnetworks whilereducingtheirsizeandcomplexity。关键词主干提取，复杂网络，地理信息，网络汇总，公共自行车，空间信息，拓扑势能，交通

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Skeleton Network Extraction and Analysis on Bicycle Sharing Networks

Skeletonnetworkextractionhasbeenadoptedunevenlyintransportationnetworkswhosenodes are always represented as spatial units. In this article, the TPks skeleton network extraction methodisproposedandappliedtobicyclesharingnetworks.Themethodaimstoreducethe networksizewhilepreservingkeytopologiesandspatialfeatures.Theauthorsquantifiedthe importanceofnodesbyanimprovedtopologypotentialalgorithm.Thespatialclusteringallows todetecthightrafficconcentrationsandallocate thenodesofeachclusteraccordingto their spatialdistribution.Then,theskeletonnetworkisconstructedbyaggregatingthemostimportant indicatedskeletonnodes.Theauthorsexaminetheskeletonnetworkcharacteristicsanddifferent spatialinformationusingtheoriginalnetworksasabenchmark.Theresultsshowthattheskeleton networkscanpreservethetopologicalandspatialinformationsimilartotheoriginalnetworks whilereducingtheirsizeandcomplexity. KEyWoRDS Backbone Extraction, Complex Network, Geographical Information, Network Summarization, Public Bicycle, Spatial Information, Topology Potential, Transportation

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving