{"id":"https://openalex.org/W2953017828","doi":"https://doi.org/10.1145/3292500.3330788","title":"SMOILE","display_name":"SMOILE","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2953017828","doi":"https://doi.org/10.1145/3292500.3330788","mag":"2953017828"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330788","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & 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/A5086146855","display_name":"Abhilash Reddy Chenreddy","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhilash Reddy Chenreddy","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045832523","display_name":"Parshan Pakiman","orcid":"https://orcid.org/0000-0001-5372-9135"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Parshan Pakiman","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078820364","display_name":"Selvaprabu Nadarajah","orcid":"https://orcid.org/0000-0001-6218-5862"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Selvaprabu Nadarajah","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045971666","display_name":"C. Ranganathan","orcid":"https://orcid.org/0000-0003-2001-578X"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ranganathan Chandrasekaran","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052105208","display_name":"Rick Abens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rick Abens","raw_affiliation_strings":["Foresight ROI, Inc., Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Foresight ROI, Inc., Chicago, IL, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5086146855"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":0.4823,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75145001,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2934","last_page":"2942"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11536","display_name":"Consumer Retail Behavior Studies","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T12384","display_name":"Customer churn and segmentation","score":0.9951000213623047,"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/computer-science","display_name":"Computer science","score":0.7093906402587891},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6695912480354309},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.570452868938446},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5093611478805542},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.41344591975212097},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3604890704154968},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3430923819541931}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7093906402587891},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6695912480354309},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.570452868938446},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5093611478805542},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.41344591975212097},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3604890704154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3430923819541931},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330788","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W122495932","https://openalex.org/W1523253953","https://openalex.org/W1951724000","https://openalex.org/W1988198833","https://openalex.org/W1999874108","https://openalex.org/W2017132602","https://openalex.org/W2024781359","https://openalex.org/W2061562262","https://openalex.org/W2098774185","https://openalex.org/W2143891888","https://openalex.org/W2147783939","https://openalex.org/W2294266477","https://openalex.org/W2396526128","https://openalex.org/W2607995933","https://openalex.org/W3103248627","https://openalex.org/W3125655541","https://openalex.org/W3187217851"],"related_works":["https://openalex.org/W4297949354","https://openalex.org/W4206669594","https://openalex.org/W2961085424","https://openalex.org/W3037422413","https://openalex.org/W2959276766","https://openalex.org/W4295941380","https://openalex.org/W260766989","https://openalex.org/W3139193008","https://openalex.org/W3170628611","https://openalex.org/W4319083788"],"abstract_inverted_index":{"Product":[0],"brands":[1],"employ":[2],"shopper":[3],"marketing":[4,16],"(SM)":[5],"strategies":[6],"to":[7,13,30,38,49,66,98,107,126,152,174,186,216,227,238],"convert":[8],"shoppers":[9],"along":[10],"the":[11,32,74,82,94,212,229,244],"path":[12],"purchase.":[14],"Traditional":[15],"mix":[17],"models":[18],"(MMMs),":[19],"which":[20],"leverage":[21],"regression":[22],"techniques":[23],"and":[24,87,90,100,120,140,148,178,181,199,205,235],"historical":[25],"data,":[26,180],"can":[27],"be":[28],"used":[29],"predict":[31],"component":[33],"of":[34,56,96,159,190,214,231,246],"sales":[35,177,198],"lift":[36,97,160,234],"due":[37,65],"SM":[39,52,138,163,200,219,233,247],"tactics.":[40],"The":[41,54],"resulting":[42],"predictive":[43],"model":[44,158],"is":[45],"a":[46,131,157,167,188,194],"critical":[47],"input":[48],"plan":[50],"future":[51,104,218],"strategies.":[53],"implementation":[55,133],"traditional":[57],"MMMs,":[58],"however,":[59],"requires":[60],"significant":[61,124],"ad-hoc":[62],"manual":[63],"intervention":[64],"their":[67],"limited":[68],"flexibility":[69],"in":[70],"(i)":[71],"explicitly":[72,175],"capturing":[73],"temporal":[75],"link":[76],"between":[77,84],"decisions;":[78],"(ii)":[79],"accounting":[80],"for":[81,117],"interaction":[83],"business":[85,108,191],"rules":[86],"past":[88],"(sales":[89],"decision)":[91],"data":[92,215],"during":[93],"attribution":[95],"SM;":[99],"(iii)":[101],"ensuring":[102],"that":[103,145],"decisions":[105],"adhere":[106],"rules.":[109,192],"These":[110],"issues":[111],"necessitate":[112],"MMMs":[113],"with":[114],"tailored":[115],"structures":[116,237],"specific":[118],"products":[119],"retailers,":[121],"each":[122],"requiring":[123],"hand-engineering":[125],"achieve":[127],"satisfactory":[128],"performance":[129],"--":[130],"major":[132],"challenge.":[134],"We":[135,221],"propose":[136],"an":[137,183,224],"Optimization":[139],"Inverse":[141],"Learning":[142],"Engine":[143],"(SMOILE)":[144],"combines":[146],"optimization":[147,184],"inverse":[149,171],"reinforcement":[150,172],"learning":[151,173],"streamline":[153],"implementation.":[154],"SMOILE":[155,210],"learns":[156],"by":[161],"viewing":[162],"tactic":[164],"choice":[165],"as":[166],"sequential":[168],"process,":[169],"leverages":[170],"couple":[176],"decision":[179,236],"employs":[182],"approach":[185],"handle":[187],"wide-array":[189],"Using":[193],"unique":[195],"dataset":[196],"containing":[197],"spend":[201],"information":[202],"across":[203],"retailers":[204],"products,":[206],"we":[207],"illustrate":[208],"how":[209],"standardizes":[211],"use":[213],"prescribe":[217],"decisions.":[220,248],"also":[222],"track":[223],"industry":[225],"benchmark":[226],"showcase":[228],"importance":[230],"encoding":[232],"mitigate":[239],"spurious":[240],"results":[241],"when":[242],"uncovering":[243],"impact":[245]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-06-27T00:00:00"}