{"id":"https://openalex.org/W2943556341","doi":"https://doi.org/10.1145/3313950.3313957","title":"Research on data visualization technology of logistics distribution system based on clustering algorithm","display_name":"Research on data visualization technology of logistics distribution system based on clustering algorithm","publication_year":2019,"publication_date":"2019-02-23","ids":{"openalex":"https://openalex.org/W2943556341","doi":"https://doi.org/10.1145/3313950.3313957","mag":"2943556341"},"language":"en","primary_location":{"id":"doi:10.1145/3313950.3313957","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3313950.3313957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image and Graphics Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008121437","display_name":"Meng Huang","orcid":"https://orcid.org/0000-0002-5045-6642"},"institutions":[{"id":"https://openalex.org/I4210098369","display_name":"Institute of Disaster Prevention","ror":"https://ror.org/00pyv1r78","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210098369","https://openalex.org/I90149893"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Huang","raw_affiliation_strings":["Institute of Disaster Prevention, HeBei, SanHe, China"],"affiliations":[{"raw_affiliation_string":"Institute of Disaster Prevention, HeBei, SanHe, China","institution_ids":["https://openalex.org/I4210098369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034535641","display_name":"Shuai Liu","orcid":"https://orcid.org/0000-0002-7115-6374"},"institutions":[{"id":"https://openalex.org/I4210098369","display_name":"Institute of Disaster Prevention","ror":"https://ror.org/00pyv1r78","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210098369","https://openalex.org/I90149893"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Liu","raw_affiliation_strings":["Institute of Disaster Prevention, HeBei, SanHe, China"],"affiliations":[{"raw_affiliation_string":"Institute of Disaster Prevention, HeBei, SanHe, China","institution_ids":["https://openalex.org/I4210098369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021353454","display_name":"Jinglei Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210098369","display_name":"Institute of Disaster Prevention","ror":"https://ror.org/00pyv1r78","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210098369","https://openalex.org/I90149893"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinglei Lin","raw_affiliation_strings":["Institute of Disaster Prevention, HeBei, SanHe, China"],"affiliations":[{"raw_affiliation_string":"Institute of Disaster Prevention, HeBei, SanHe, China","institution_ids":["https://openalex.org/I4210098369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008121437"],"corresponding_institution_ids":["https://openalex.org/I4210098369"],"apc_list":null,"apc_paid":null,"fwci":0.1585,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52152794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"565","issue":null,"first_page":"114","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9599000215530396,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8451525568962097},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7702398300170898},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.6617542505264282},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6461892127990723},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6327961683273315},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4326379895210266},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.4305286705493927},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34295374155044556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2002459168434143}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8451525568962097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7702398300170898},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6617542505264282},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6461892127990723},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6327961683273315},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4326379895210266},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4305286705493927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34295374155044556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2002459168434143},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3313950.3313957","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3313950.3313957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image and Graphics Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W1997874197","https://openalex.org/W2122584464","https://openalex.org/W3106407256"],"related_works":["https://openalex.org/W2013728941","https://openalex.org/W4225274103","https://openalex.org/W2579659702","https://openalex.org/W2154046714","https://openalex.org/W1965329638","https://openalex.org/W2189613078","https://openalex.org/W2923661510","https://openalex.org/W1574055964","https://openalex.org/W2542318691","https://openalex.org/W3160708108"],"abstract_inverted_index":{"This":[0],"paper":[1],"takes":[2],"the":[3,12,17,23,30,42,50,62,75,91,98,101],"logistics":[4,95],"distribution":[5,63,94],"record":[6],"of":[7,32,45,93,100],"Yifeng":[8],"Weiye":[9],"Group":[10],"for":[11,87],"past":[13],"two":[14],"years":[15],"as":[16],"basic":[18],"research":[19],"unit.":[20],"By":[21],"exploring":[22],"relationship":[24],"between":[25],"data":[26,44],"fields,":[27],"we":[28,54],"use":[29,55],"idea":[31],"adaptive":[33],"clustering":[34,38,52],"algorithm":[35],"and":[36,57,65,84,96],"spatial":[37],"analysis":[39,83],"to":[40,60,73,89],"process":[41],"attribute":[43],"transportation":[46],"capacity[8].":[47],"Basing":[48],"on":[49],"obtained":[51],"results,":[53],"Python":[56],"PHP":[58],"technology":[59],"optimize":[61,97],"area,":[64],"finally":[66],"design":[67],"an":[68],"effective":[69],"visual":[70],"expression":[71],"method":[72],"obtain":[74],"traffic":[76],"situation":[77],"knowledge.":[78],"We":[79],"can":[80],"provide":[81],"relevant":[82],"technical":[85],"support":[86],"enterprises":[88],"improve":[90],"efficiency":[92],"structure":[99],"industrial":[102],"chain.":[103]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
