{"id":"https://openalex.org/W4396843795","doi":"https://doi.org/10.1145/3589335.3641244","title":"Discrete Choice and Applications","display_name":"Discrete Choice and Applications","publication_year":2024,"publication_date":"2024-05-12","ids":{"openalex":"https://openalex.org/W4396843795","doi":"https://doi.org/10.1145/3589335.3641244"},"language":"en","primary_location":{"id":"doi:10.1145/3589335.3641244","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3641244","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3641244","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3641244","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078401676","display_name":"Flavio Chierichetti","orcid":"https://orcid.org/0000-0001-8261-9058"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Flavio Chierichetti","raw_affiliation_strings":["Sapienza University, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0001-8261-9058","affiliations":[{"raw_affiliation_string":"Sapienza University, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101772779","display_name":"Ravi Kumar","orcid":"https://orcid.org/0000-0002-2203-2586"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi Kumar","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2203-2586","affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068021191","display_name":"Andrew Tomkins","orcid":"https://orcid.org/0000-0002-1611-9255"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Tomkins","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1611-9255","affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078401676"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0472699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1258","last_page":"1259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9926999807357788,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6671876907348633},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.6407454013824463},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.601529061794281},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.5692492127418518},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5630530118942261},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5554919838905334},{"id":"https://openalex.org/keywords/discrete-choice","display_name":"Discrete choice","score":0.5494040846824646},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.5404028296470642},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5116360783576965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5112214088439941},{"id":"https://openalex.org/keywords/management-science","display_name":"Management science","score":0.3621191382408142},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.23470544815063477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10260313749313354},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10225951671600342}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6671876907348633},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.6407454013824463},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.601529061794281},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.5692492127418518},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5630530118942261},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5554919838905334},{"id":"https://openalex.org/C190669063","wikidata":"https://www.wikidata.org/wiki/Q5282043","display_name":"Discrete choice","level":2,"score":0.5494040846824646},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.5404028296470642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5116360783576965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5112214088439941},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3621191382408142},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.23470544815063477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10260313749313354},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10225951671600342},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589335.3641244","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3641244","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3641244","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589335.3641244","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3641244","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3641244","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396843795.pdf"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W123430343","https://openalex.org/W1550812296","https://openalex.org/W1986433688","https://openalex.org/W2004657139","https://openalex.org/W2338772862","https://openalex.org/W3210418234","https://openalex.org/W6692661175","https://openalex.org/W6713156835","https://openalex.org/W6751816427"],"related_works":["https://openalex.org/W1600556093","https://openalex.org/W3143873299","https://openalex.org/W1561002350","https://openalex.org/W3097028628","https://openalex.org/W4401768057","https://openalex.org/W2349244999","https://openalex.org/W4385351990","https://openalex.org/W4320082066","https://openalex.org/W1994479053","https://openalex.org/W2074948550"],"abstract_inverted_index":{"Modern":[0],"machine":[1,141],"learning":[2,142,165],"and":[3,11,51,54,82,134,149,162,181],"AI":[4],"have":[5,89],"revolutionized":[6],"the":[7,21,37,58,72,106,117,129,132,159,179,193],"generation":[8],"of":[9,33,42,74,86,105,109,131,140,156,164,168],"ranking":[10],"recommendations":[12],"across":[13],"many":[14,104],"domains,":[15],"taking":[16],"data-driven":[17],"approaches":[18],"to":[19,29,49,65,91,97,116,137,189],"inferring":[20],"candidate":[22],"items":[23],"a":[24,83,154],"user":[25],"is":[26,47],"most":[27],"likely":[28],"select.":[30],"The":[31],"theory":[32,46],"discrete":[34,75,110,184],"choice":[35,111,185],"provides":[36],"theoretical":[38],"underpinnings":[39],"for":[40,68],"study":[41],"these":[43],"problems.":[44],"This":[45],"central":[48,107],"economics":[50,63],"behavioral":[52],"sciences,":[53],"was":[55],"recognized":[56],"with":[57],"2000":[59],"Nobel":[60],"Prize":[61],"in":[62,79,93,100,119,178,192],"awarded":[64],"Daniel":[66],"McFadden":[67],"his":[69],"work":[70,78],"on":[71],"analysis":[73],"choice.":[76,169],"Classical":[77],"this":[80,123],"area,":[81],"wide":[84],"range":[85],"recent":[87],"advances,":[88],"much":[90],"offer":[92],"thinking":[94],"about":[95,158],"how":[96],"support":[98],"users":[99],"making":[101],"choices.":[102],"However,":[103],"tools":[108,139,186],"are":[112,187],"not":[113],"broadly":[114],"known":[115],"researchers":[118],"our":[120],"area.":[121],"In":[122],"proposed":[124],"tutorial,":[125],"we":[126,172],"will":[127,152,173],"cover":[128,153],"foundations":[130],"field,":[133,180],"provide":[135],"connections":[136],"common":[138],"such":[143],"as":[144],"logistic":[145],"regression,":[146,148],"multinomial":[147],"softmax.":[150],"We":[151],"number":[155],"results":[157],"representational":[160],"power":[161],"complexity":[163],"various":[166],"models":[167],"And":[170],"finally,":[171],"suggest":[174],"both":[175],"open":[176],"problems":[177,191],"areas":[182],"where":[183],"relevant":[188],"key":[190],"Web":[194],"Conference":[195],"community.":[196]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
