{"id":"https://openalex.org/W2798309468","doi":"https://doi.org/10.1145/3183713.3196923","title":"A Query Engine for Probabilistic Preferences","display_name":"A Query Engine for Probabilistic Preferences","publication_year":2018,"publication_date":"2018-05-25","ids":{"openalex":"https://openalex.org/W2798309468","doi":"https://doi.org/10.1145/3183713.3196923","mag":"2798309468"},"language":"en","primary_location":{"id":"doi:10.1145/3183713.3196923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3183713.3196923","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3183713.3196923","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Management of Data","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/10.1145/3183713.3196923","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043358045","display_name":"Uzi Cohen","orcid":null},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Uzi Cohen","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047636495","display_name":"Batya Kenig","orcid":"https://orcid.org/0000-0001-6349-128X"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Batya Kenig","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001717508","display_name":"Haoyue Ping","orcid":"https://orcid.org/0000-0002-2694-3301"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoyue Ping","raw_affiliation_strings":["Drexel University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006706357","display_name":"Benny Kimelfeld","orcid":"https://orcid.org/0000-0002-7156-1572"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Benny Kimelfeld","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082830839","display_name":"Julia Stoyanovich","orcid":"https://orcid.org/0000-0002-1587-0450"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Julia Stoyanovich","raw_affiliation_strings":["Drexel University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5043358045"],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":0.4974,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62322799,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1509","last_page":"1524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9973000288009644,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.9825999736785889,"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/computer-science","display_name":"Computer science","score":0.7927125692367554},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6911033391952515},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6484028697013855},{"id":"https://openalex.org/keywords/inference-engine","display_name":"Inference engine","score":0.5467045903205872},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.5020992755889893},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.4474954307079315},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.44072476029396057},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4244036078453064},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.41999152302742004},{"id":"https://openalex.org/keywords/conjunctive-query","display_name":"Conjunctive query","score":0.4172613024711609},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38596847653388977},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32058072090148926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.250510573387146},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.15142253041267395}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7927125692367554},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6911033391952515},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6484028697013855},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.5467045903205872},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.5020992755889893},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.4474954307079315},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.44072476029396057},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4244036078453064},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.41999152302742004},{"id":"https://openalex.org/C65647387","wikidata":"https://www.wikidata.org/wiki/Q1781706","display_name":"Conjunctive query","level":3,"score":0.4172613024711609},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38596847653388977},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32058072090148926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.250510573387146},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.15142253041267395}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3183713.3196923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3183713.3196923","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3183713.3196923","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3183713.3196923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3183713.3196923","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3183713.3196923","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G355211256","display_name":null,"funder_award_id":"5921551","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"},{"id":"https://openalex.org/G4522459015","display_name":null,"funder_award_id":"1464327","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5241881333","display_name":null,"funder_award_id":"1741047","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5606265171","display_name":"BSF: 2014391: Aggregation Methods for Partial Preferences Overview.","funder_award_id":"1539856","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6097872218","display_name":null,"funder_award_id":"2014391","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"},{"id":"https://openalex.org/G7315415636","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"},{"id":"https://openalex.org/G8933656170","display_name":"SCH:INT: Collaborative Research: Deep Sense: Interpretable Deep Learning for Zero-effort Phenotype Sensing and Its Application to Sleep Medicine","funder_award_id":"2014391","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2798309468.pdf","grobid_xml":"https://content.openalex.org/works/W2798309468.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1550469973","https://openalex.org/W1574648663","https://openalex.org/W1605745662","https://openalex.org/W1773019610","https://openalex.org/W1920496255","https://openalex.org/W1942909375","https://openalex.org/W1964912686","https://openalex.org/W1976743651","https://openalex.org/W1979682978","https://openalex.org/W1982432923","https://openalex.org/W1985514943","https://openalex.org/W1991593950","https://openalex.org/W2026411617","https://openalex.org/W2027752285","https://openalex.org/W2046265151","https://openalex.org/W2051834357","https://openalex.org/W2063445365","https://openalex.org/W2078686663","https://openalex.org/W2081186682","https://openalex.org/W2097233310","https://openalex.org/W2109555487","https://openalex.org/W2114523181","https://openalex.org/W2114887670","https://openalex.org/W2126500482","https://openalex.org/W2135036692","https://openalex.org/W2136137885","https://openalex.org/W2146511318","https://openalex.org/W2150735632","https://openalex.org/W2162142896","https://openalex.org/W2188252507","https://openalex.org/W2295231932","https://openalex.org/W2299232349","https://openalex.org/W2305586808","https://openalex.org/W2319151433","https://openalex.org/W2338322935","https://openalex.org/W2422865028","https://openalex.org/W2495505314","https://openalex.org/W2604431341","https://openalex.org/W2952812825","https://openalex.org/W3103181292","https://openalex.org/W4300564796"],"related_works":["https://openalex.org/W2383168085","https://openalex.org/W1901149804","https://openalex.org/W2387635197","https://openalex.org/W3174970460","https://openalex.org/W1639806124","https://openalex.org/W32512226","https://openalex.org/W1729122178","https://openalex.org/W2264386184","https://openalex.org/W206482712","https://openalex.org/W2288512712"],"abstract_inverted_index":{"Models":[0],"of":[1,15,52,55,66,70,78,99,131,136],"uncertain":[2,32],"preferences,":[3],"such":[4],"as":[5,34,185],"Mallows,":[6],"have":[7],"been":[8,28],"extensively":[9],"studied":[10],"due":[11],"to":[12,187],"their":[13],"plethora":[14],"application":[16],"domains.":[17],"In":[18,58],"a":[19,22,38,67,79,114,178,188,193],"recent":[20],"work,":[21],"conceptual":[23],"and":[24,108,123,139,168],"theoretical":[25],"framework":[26],"has":[27],"proposed":[29],"for":[30,118],"supporting":[31],"preferences":[33,86],"first-class":[35],"citizens":[36],"in":[37,95,134,158],"relational":[39,88],"database.":[40],"The":[41],"resulting":[42],"database":[43],"is":[44],"probabilistic,":[45],"and,":[46],"consequently,":[47],"query":[48,56,80,179],"evaluation":[49,167],"entails":[50],"inference":[51,116,156,195],"marginal":[53],"probabilities":[54],"answers.":[57],"this":[59,71],"paper,":[60],"we":[61,162],"embark":[62],"on":[63,151],"the":[64,96,100,129,132,159],"challenge":[65],"practical":[68],"realization":[69],"framework.":[72],"We":[73,111,143],"first":[74],"describe":[75],"an":[76,164],"implementation":[77,191],"engine":[81,180],"that":[82,125,148,170],"supports":[83],"querying":[84],"probabilistic":[85,183],"alongside":[87],"data.":[89],"Our":[90],"system":[91],"accommodates":[92],"preference":[93],"distributions":[94],"general":[97],"form":[98],"Repeated":[101],"Insertion":[102],"Model":[103],"(RIM),":[104],"which":[105],"generalizes":[106],"Mallows":[107],"other":[109],"models.":[110],"then":[112],"devise":[113],"novel":[115],"algorithm":[117],"conjunctive":[119],"queries":[120],"over":[121],"RIM,":[122],"show":[124],"it":[126],"significantly":[127],"outperforms":[128],"state":[130],"art":[133],"terms":[135],"both":[137],"asymptotic":[138],"empirical":[140],"execution":[141],"cost.":[142],"also":[144],"develop":[145],"performance":[146,172],"optimizations":[147],"are":[149],"based":[150],"sharing":[152],"computation":[153],"among":[154],"different":[155],"tasks":[157],"workload.":[160],"Finally,":[161],"conduct":[163],"extensive":[165],"experimental":[166],"demonstrate":[169],"clear":[171],"benefits":[173],"can":[174],"be":[175],"realized":[176],"by":[177],"with":[181,192],"built-in":[182],"inference,":[184],"compared":[186],"stand":[189],"alone":[190],"black-box":[194],"solver.":[196]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}