{"id":"https://openalex.org/W1983953676","doi":"https://doi.org/10.1109/dbta.2010.5659081","title":"Application of Data Mining Technique in Customer Segmentation of Shipping Enterprises","display_name":"Application of Data Mining Technique in Customer Segmentation of Shipping Enterprises","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W1983953676","doi":"https://doi.org/10.1109/dbta.2010.5659081","mag":"1983953676"},"language":"en","primary_location":{"id":"doi:10.1109/dbta.2010.5659081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dbta.2010.5659081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 2nd International Workshop on Database Technology and Applications","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/A5100753852","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-4088-7617"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Wang","raw_affiliation_strings":["School of Energy and Power Engineering, Wuhan University of Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Energy and Power Engineering, Wuhan University of Technology, Shanghai, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113337082","display_name":"Shidong Fan","orcid":"https://orcid.org/0000-0001-7301-6351"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shidong Fan","raw_affiliation_strings":["School of Energy and Power Engineering, Wuhan University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Energy and Power Engineering, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100753852"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":2.5562,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9354067,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"11","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14139","display_name":"E-commerce and Technology Innovations","score":0.7879999876022339,"subfield":{"id":"https://openalex.org/subfields/1403","display_name":"Business and International Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T14139","display_name":"E-commerce and Technology Innovations","score":0.7879999876022339,"subfield":{"id":"https://openalex.org/subfields/1403","display_name":"Business and International Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.7731000185012817,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6284866333007812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6160776615142822},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5941012501716614},{"id":"https://openalex.org/keywords/customer-relationship-management","display_name":"Customer relationship management","score":0.5368398427963257},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.5117282867431641},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48232385516166687},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4624163806438446},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.44301581382751465},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33774706721305847},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2787955105304718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2499573826789856},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.24209240078926086},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.14353632926940918},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.08323976397514343}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6284866333007812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6160776615142822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5941012501716614},{"id":"https://openalex.org/C98825075","wikidata":"https://www.wikidata.org/wiki/Q485643","display_name":"Customer relationship management","level":2,"score":0.5368398427963257},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.5117282867431641},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48232385516166687},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4624163806438446},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.44301581382751465},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33774706721305847},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2787955105304718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2499573826789856},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.24209240078926086},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.14353632926940918},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.08323976397514343}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dbta.2010.5659081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dbta.2010.5659081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 2nd International Workshop on Database Technology and Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W208128215","https://openalex.org/W2051224630","https://openalex.org/W2140190241","https://openalex.org/W2351989790","https://openalex.org/W2375201626","https://openalex.org/W3166095749","https://openalex.org/W4285719527","https://openalex.org/W6680704940","https://openalex.org/W6795749741","https://openalex.org/W7052445662"],"related_works":["https://openalex.org/W2592395359","https://openalex.org/W2045342254","https://openalex.org/W2535231171","https://openalex.org/W1501331687","https://openalex.org/W4255512592","https://openalex.org/W4205247302","https://openalex.org/W2468652214","https://openalex.org/W2501551404","https://openalex.org/W2326647871","https://openalex.org/W1504527458"],"abstract_inverted_index":{"Previous":[0],"studies":[1],"have":[2],"focused":[3],"on":[4,21,49],"serveral":[5],"aspects":[6],"of":[7,17,25,52,64,66,78,106,123],"CRM":[8,40,121],"(Customer":[9],"Relationship":[10],"Management).":[11],"However,":[12],"there":[13],"is":[14,111],"a":[15],"lack":[16],"research":[18],"that":[19],"focuses":[20],"the":[22,50,62,72,75,95,104,114,120],"customer":[23],"segmentation":[24,65],"shipping":[26,67,124],"enterprises":[27],"using":[28,88,98],"data":[29,57,77],"mining.":[30],"Data":[31],"mining":[32,71],"technology":[33],"can":[34],"be":[35],"used":[36],"to":[37,41,103,112],"in":[38,56,74],"modern":[39],"greatly":[42],"enhance":[43],"it":[44],"function":[45],"and":[46,54,92,118],"efficiency.":[47],"Based":[48],"technologies":[51],"clustering":[53],"classification":[55],"mining,":[58],"this":[59],"paper":[60],"discusses":[61],"method":[63],"enterprises'":[68],"customers":[69],"by":[70],"information":[73],"mass":[76],"documentation":[79],"database.":[80],"That":[81],"is,":[82],"we":[83],"cluster":[84,89],"history":[85],"freight":[86],"instances":[87],"algorithm":[90],"first,":[91],"then":[93],"classify":[94],"new":[96],"instance":[97],"Bayesian":[99],"network":[100],"classifier":[101],"according":[102],"results":[105],"former":[107],"steps.":[108],"The":[109],"purpose":[110],"support":[113],"marketing":[115],"departments'":[116],"decision-making,":[117],"improve":[119],"level":[122],"enterprises.":[125]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
