{"id":"https://openalex.org/W2120610831","doi":"https://doi.org/10.1109/icdm.2003.1250942","title":"MPIS: maximal-profit item selection with cross-selling considerations","display_name":"MPIS: maximal-profit item selection with cross-selling considerations","publication_year":2004,"publication_date":"2004-03-30","ids":{"openalex":"https://openalex.org/W2120610831","doi":"https://doi.org/10.1109/icdm.2003.1250942","mag":"2120610831"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","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/A5049858061","display_name":"Raymond Chi-Wing Wong","orcid":"https://orcid.org/0000-0001-7045-6503"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Raymond Chi-Wing Wong","raw_affiliation_strings":["Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China","Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110164824","display_name":"Ada Wai-Chee Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ada Wai-Chee Fu","raw_affiliation_strings":["Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China","Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018822961","display_name":"Kaili Wang","orcid":"https://orcid.org/0009-0004-9008-2069"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"K. Wang","raw_affiliation_strings":["Department of Computer Science, Simon Fraser University, Canada","Simon Fraser University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Simon Fraser University, Canada","institution_ids":["https://openalex.org/I18014758"]},{"raw_affiliation_string":"Simon Fraser University","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049858061"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":9.6897,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.97473766,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"371","last_page":"378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9067000150680542,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.7776540517807007},{"id":"https://openalex.org/keywords/profit","display_name":"Profit (economics)","score":0.6562018394470215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5971986651420593},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5068214535713196},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.4911455810070038},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.47719013690948486},{"id":"https://openalex.org/keywords/quadratic-programming","display_name":"Quadratic programming","score":0.4640684723854065},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4540482461452484},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4128514528274536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3128776550292969},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3021950125694275},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.10131418704986572},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.06325805187225342}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.7776540517807007},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.6562018394470215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5971986651420593},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5068214535713196},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.4911455810070038},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.47719013690948486},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.4640684723854065},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4540482461452484},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4128514528274536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3128776550292969},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3021950125694275},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.10131418704986572},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.06325805187225342},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icdm.2003.1250942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.131.1644","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.1644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.sfu.ca/~wangk/pub/icdm03.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.176.4163","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.176.4163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.ust.hk/%7Eraywong/paper/icdm03-mpis.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.75.7682","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.7682","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.cuhk.edu.hk/~adafu/Pub/ICDM03.ps","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W20184837","https://openalex.org/W135055223","https://openalex.org/W202383464","https://openalex.org/W612528811","https://openalex.org/W1484413656","https://openalex.org/W1493647235","https://openalex.org/W1494474111","https://openalex.org/W1506285740","https://openalex.org/W1512482816","https://openalex.org/W1570697393","https://openalex.org/W1571438983","https://openalex.org/W1577789187","https://openalex.org/W1603194053","https://openalex.org/W1979943645","https://openalex.org/W1995246641","https://openalex.org/W2005069425","https://openalex.org/W2010247018","https://openalex.org/W2011039300","https://openalex.org/W2064853889","https://openalex.org/W2068986562","https://openalex.org/W2102423866","https://openalex.org/W2138621811","https://openalex.org/W2152316886","https://openalex.org/W2166559705","https://openalex.org/W2301746362","https://openalex.org/W2476096155","https://openalex.org/W2751335644","https://openalex.org/W2751593060","https://openalex.org/W3202531429","https://openalex.org/W4252403066","https://openalex.org/W4285719527","https://openalex.org/W6600858232","https://openalex.org/W6605513013","https://openalex.org/W6610072603","https://openalex.org/W6628750762","https://openalex.org/W6629469108","https://openalex.org/W6634201796","https://openalex.org/W6634266418","https://openalex.org/W6653046663","https://openalex.org/W7029283403"],"related_works":["https://openalex.org/W2751920613","https://openalex.org/W2415164632","https://openalex.org/W2238349241","https://openalex.org/W3036464408","https://openalex.org/W2020990755","https://openalex.org/W2377851227","https://openalex.org/W4293088966","https://openalex.org/W2366868484","https://openalex.org/W2917463375","https://openalex.org/W2155219672"],"abstract_inverted_index":{"In":[0,121],"the":[1,34,63,67,88,91,94,105,111,142],"literature":[2],"of":[3,33,58,69,77,93,100,141],"data":[4],"mining,":[5],"many":[6],"different":[7],"algorithms":[8],"for":[9,36],"association":[10,24,37,101],"rule":[11,96,102],"mining":[12],"have":[13],"been":[14],"proposed.":[15],"However,":[16],"there":[17],"is":[18,49,53,80,125],"relatively":[19],"little":[20],"study":[21],"on":[22],"how":[23],"rules":[25,38],"can":[26,61,113],"aid":[27],"in":[28],"more":[29],"specific":[30],"targets.":[31],"One":[32],"applications":[35],"-":[39,48,97],"maximal-profit":[40],"item":[41],"selection":[42],"with":[43,66,90],"cross-selling":[44,106],"effect":[45],"(MPIS)":[46],"problem":[47,52,79,89,112],"investigated.":[50],"The":[51],"about":[54],"selecting":[55],"a":[56,74,84,98,117,131],"subset":[57],"items,":[59],"which":[60],"give":[62],"maximal":[64],"profit":[65],"consideration":[68,92],"cross-selling.":[70],"We":[71,82,108],"prove":[72],"that":[73,110,139],"simple":[75],"version":[76],"this":[78],"NP-hard.":[81],"propose":[83,130],"new":[85],"approach":[86],"to":[87,103,116,137],"loss":[95],"kind":[99],"model":[104],"effect.":[107],"show":[109,138],"be":[114],"transformed":[115],"quadratic":[118,123],"programming":[119,124],"problem.":[120],"case":[122],"not":[126],"applicable,":[127],"we":[128],"also":[129],"heuristic":[132],"approach.":[133],"Experiments":[134],"are":[135,145],"conducted":[136],"both":[140],"proposed":[143],"methods":[144],"highly":[146],"effective":[147],"and":[148],"efficient.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}