{"id":"https://openalex.org/W4376852402","doi":"https://doi.org/10.1145/3573942.3573951","title":"Express-related Counterfeit Cigarette Crime Prediction with Imbalanced Data-based Machine Learning Techniques","display_name":"Express-related Counterfeit Cigarette Crime Prediction with Imbalanced Data-based Machine Learning Techniques","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4376852402","doi":"https://doi.org/10.1145/3573942.3573951"},"language":"en","primary_location":{"id":"doi:10.1145/3573942.3573951","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3573951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","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/A5100431776","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-3131-7401"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Liu","raw_affiliation_strings":["School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074234673","display_name":"Rong-Yao Xu","orcid":"https://orcid.org/0000-0003-4666-6580"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong-yao Xu","raw_affiliation_strings":["School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088231065","display_name":"Lang-chao Qiao","orcid":"https://orcid.org/0000-0003-0607-3131"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lang-chao Qiao","raw_affiliation_strings":["Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China"],"affiliations":[{"raw_affiliation_string":"Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001826823","display_name":"Jin-lu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin-lu Wang","raw_affiliation_strings":["Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China"],"affiliations":[{"raw_affiliation_string":"Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023995928","display_name":"Bao-hong Gao","orcid":"https://orcid.org/0000-0002-1588-0704"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bao-hong Gao","raw_affiliation_strings":["Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China"],"affiliations":[{"raw_affiliation_string":"Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108837287","display_name":"Xin-gang Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin-gang Yang","raw_affiliation_strings":["Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China"],"affiliations":[{"raw_affiliation_string":"Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002197723","display_name":"Wentao Feng","orcid":"https://orcid.org/0000-0001-9737-3505"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen-tao Feng","raw_affiliation_strings":["Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China"],"affiliations":[{"raw_affiliation_string":"Division of Monopoly Administration, Shaanxi Branch of China National Tobacco Corporation, China","institution_ids":["https://openalex.org/I2800556661"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100431776"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.1327,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56601621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"57","last_page":"62"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9952999949455261,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9603999853134155,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.9539999961853027,"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/counterfeit","display_name":"Counterfeit","score":0.8274070620536804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.775334358215332},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7219640016555786},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.6494392156600952},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.564715564250946},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5203830003738403},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5189313888549805},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5097402930259705},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46122604608535767},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4559297263622284},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37899696826934814}],"concepts":[{"id":"https://openalex.org/C2779356469","wikidata":"https://www.wikidata.org/wiki/Q502918","display_name":"Counterfeit","level":2,"score":0.8274070620536804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.775334358215332},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7219640016555786},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.6494392156600952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.564715564250946},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5203830003738403},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5189313888549805},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5097402930259705},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46122604608535767},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4559297263622284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37899696826934814},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573942.3573951","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3573951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7400000095367432,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2892562420","https://openalex.org/W2958825559","https://openalex.org/W3043942921","https://openalex.org/W3097882740","https://openalex.org/W3141022462","https://openalex.org/W3163311383","https://openalex.org/W3165477009","https://openalex.org/W4200494353","https://openalex.org/W4206811075","https://openalex.org/W4289821942","https://openalex.org/W4292074531"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"The":[0,155],"number":[1],"of":[2,29,44,88,132,157,180],"cigarette-related":[3,147,153],"packages":[4,7,34],"and":[5,54,82,93,95,126,145,169],"normal":[6,143],"is":[8,63,160],"often":[9],"extremely":[10],"unbalanced":[11],"in":[12,19,138],"practice,":[13],"this":[14,40],"characteristic":[15],"must":[16],"be":[17,36],"considered":[18],"the":[20,27,56,66,85,96,121,130,164,170,181],"express-related":[21,57],"counterfeit":[22,58,136],"cigarette":[23,59],"crime":[24,60],"prediction,":[25],"otherwise":[26],"performance":[28,156],"prediction":[30,61],"model":[31,62,123],"on":[32,110],"unknown":[33],"will":[35],"affected":[37],"badly.":[38],"In":[39,65,79],"paper,":[41],"an":[42],"approach":[43],"using":[45,163],"SMOTE-ENN":[46],"technology":[47],"to":[48,128,166],"deal":[49],"with":[50],"imbalanced":[51],"express":[52,89,139],"data":[53,70,90,114,140],"establish":[55],"proposed.":[64],"preprocessing":[67],"stage,":[68,84],"original":[69],"sets":[71],"are":[72,91,99,115,172],"structured":[73],"by":[74,102,117],"Chinese":[75],"word":[76],"segmentation":[77],"method.":[78],"feature":[80,103],"calculation":[81],"analysis":[83],"spatio-temporal":[86],"features":[87,98],"calculated":[92],"analyzed,":[94],"optimal":[97,111],"further":[100],"obtained":[101,116],"reduction":[104],"algorithm":[105],"named":[106],"PCA.":[107],"Next,":[108],"based":[109],"features,":[112],"balanced":[113],"mixed":[118],"sampling.":[119],"Finally,":[120],"classifier":[122],"was":[124],"trained":[125],"optimized":[127],"predict":[129],"probability":[131],"a":[133],"package":[134],"containing":[135],"cigarettes":[137],"including":[141],"2851":[142],"samples":[144,148],"285":[146],"randomly":[149],"selected":[150],"from":[151],"3077":[152],"samples.":[154],"all":[158],"classifiers":[159],"improved":[161],"after":[162],"SMOTE_ENN":[165],"balance":[167],"datasets,":[168],"indicators":[171],"above":[173],"98%.":[174],"Experimental":[175],"results":[176],"demonstrate":[177],"feasibility,":[178],"effectiveness":[179],"proposed":[182],"approach.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}