{"id":"https://openalex.org/W2608387285","doi":"https://doi.org/10.1145/3041021.3054195","title":"Numerical Facet Range Partition","display_name":"Numerical Facet Range Partition","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2608387285","doi":"https://doi.org/10.1145/3041021.3054195","mag":"2608387285"},"language":"en","primary_location":{"id":"doi:10.1145/3041021.3054195","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3041021.3054195","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3041021.3054195","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100775515","display_name":"Xueqing Liu","orcid":"https://orcid.org/0000-0003-4916-0884"},"institutions":[{"id":"https://openalex.org/I183874917","display_name":"Urbana University","ror":"https://ror.org/04kp3hw27","country_code":"US","type":"education","lineage":["https://openalex.org/I183874917"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xueqing Liu","raw_affiliation_strings":["UIUC, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"UIUC, Urbana, IL, USA","institution_ids":["https://openalex.org/I183874917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028518494","display_name":"ChengXiang Zhai","orcid":"https://orcid.org/0000-0002-6434-3702"},"institutions":[{"id":"https://openalex.org/I183874917","display_name":"Urbana University","ror":"https://ror.org/04kp3hw27","country_code":"US","type":"education","lineage":["https://openalex.org/I183874917"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chengxiang Zhai","raw_affiliation_strings":["UIUC, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"UIUC, Urbana, IL, USA","institution_ids":["https://openalex.org/I183874917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100962894","display_name":"Wei Han","orcid":null},"institutions":[{"id":"https://openalex.org/I1330693074","display_name":"Walmart (United States)","ror":"https://ror.org/04j0gge90","country_code":"US","type":"company","lineage":["https://openalex.org/I1330693074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Han","raw_affiliation_strings":["WalmartLabs, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"WalmartLabs, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1330693074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103267293","display_name":"Onur G\u00fcng\u00f6r","orcid":"https://orcid.org/0000-0002-1605-3495"},"institutions":[{"id":"https://openalex.org/I1330693074","display_name":"Walmart (United States)","ror":"https://ror.org/04j0gge90","country_code":"US","type":"company","lineage":["https://openalex.org/I1330693074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Onur Gungor","raw_affiliation_strings":["WalmartLabs, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"WalmartLabs, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1330693074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100775515"],"corresponding_institution_ids":["https://openalex.org/I183874917"],"apc_list":null,"apc_paid":null,"fwci":0.4836,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71555665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"662","last_page":"671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9965999722480774,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9965999722480774,"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/T11106","display_name":"Data Management and Algorithms","score":0.9962999820709229,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.994700014591217,"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/partition","display_name":"Partition (number theory)","score":0.7558236122131348},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7061508297920227},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6060119271278381},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5617976188659668},{"id":"https://openalex.org/keywords/facet","display_name":"Facet (psychology)","score":0.5474626421928406},{"id":"https://openalex.org/keywords/partition-problem","display_name":"Partition problem","score":0.5108723044395447},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4418550431728363},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4389355182647705},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3875771462917328},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35299551486968994},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3495813012123108},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19009935855865479},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10053607821464539}],"concepts":[{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.7558236122131348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7061508297920227},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6060119271278381},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5617976188659668},{"id":"https://openalex.org/C43122875","wikidata":"https://www.wikidata.org/wiki/Q5428522","display_name":"Facet (psychology)","level":4,"score":0.5474626421928406},{"id":"https://openalex.org/C35995877","wikidata":"https://www.wikidata.org/wiki/Q1065968","display_name":"Partition problem","level":3,"score":0.5108723044395447},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4418550431728363},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4389355182647705},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3875771462917328},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35299551486968994},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3495813012123108},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19009935855865479},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10053607821464539},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C187288502","wikidata":"https://www.wikidata.org/wiki/Q641118","display_name":"Personality","level":2,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C2865642","wikidata":"https://www.wikidata.org/wiki/Q378132","display_name":"Big Five personality traits","level":3,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3041021.3054195","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3041021.3054195","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3041021.3054195","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3041021.3054195","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4399999976158142}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1553682320","https://openalex.org/W1589269155","https://openalex.org/W1822348499","https://openalex.org/W1949212457","https://openalex.org/W1967498673","https://openalex.org/W1968927634","https://openalex.org/W1979020924","https://openalex.org/W1982304915","https://openalex.org/W1992549066","https://openalex.org/W1998381498","https://openalex.org/W2002766161","https://openalex.org/W2014569888","https://openalex.org/W2025533349","https://openalex.org/W2029129758","https://openalex.org/W2029223910","https://openalex.org/W2038975839","https://openalex.org/W2046437776","https://openalex.org/W2048045485","https://openalex.org/W2069870183","https://openalex.org/W2078950386","https://openalex.org/W2099561919","https://openalex.org/W2101751183","https://openalex.org/W2105481243","https://openalex.org/W2108898822","https://openalex.org/W2127176025","https://openalex.org/W2135046866","https://openalex.org/W2137095063","https://openalex.org/W2155211665","https://openalex.org/W2169369819","https://openalex.org/W2171074980","https://openalex.org/W3085162807","https://openalex.org/W4234292174","https://openalex.org/W4238998169","https://openalex.org/W6638337754","https://openalex.org/W6682975109","https://openalex.org/W6843735874"],"related_works":["https://openalex.org/W1549987457","https://openalex.org/W2025912669","https://openalex.org/W1977789739","https://openalex.org/W2014615094","https://openalex.org/W2047470742","https://openalex.org/W2351778335","https://openalex.org/W2497180562","https://openalex.org/W2379495598","https://openalex.org/W2767131998","https://openalex.org/W4240458717"],"abstract_inverted_index":{"Faceted":[0],"navigation":[1],"is":[2,12],"a":[3,86,117,122],"very":[4],"useful":[5,14],"component":[6],"in":[7,37],"today's":[8],"search":[9,98,119],"engines.":[10],"It":[11],"especially":[13],"when":[15],"user":[16],"has":[17,31,43],"an":[18,78,91],"exploratory":[19],"information":[20],"need":[21],"or":[22],"prefer":[23],"certain":[24],"attribute":[25],"values":[26],"than":[27],"others.":[28],"Existing":[29],"work":[30,42],"tried":[32],"to":[33,94,97],"optimize":[34,110],"faceted":[35],"systems":[36],"many":[38],"aspects,":[39],"but":[40],"little":[41],"been":[44],"done":[45],"on":[46,68,116],"optimizing":[47],"numerical":[48,69],"facet":[49,70],"ranges":[50,53],"(e.g.,":[51],"price":[52],"of":[54,85],"product).":[55],"In":[56],"this":[57],"paper,":[58],"we":[59,89],"introduce":[60],"for":[61],"the":[62,65,111],"first":[63],"time":[64],"research":[66],"problem":[67],"range":[71,105],"partition":[72,87,106],"and":[73],"formally":[74],"frame":[75],"it":[76],"as":[77],"optimization":[79],"problem.":[80],"To":[81],"enable":[82],"quantitative":[83],"evaluation":[84,92],"algorithm,":[88],"propose":[90,103],"metric":[93],"be":[95],"applied":[96],"engine":[99,125],"logs.":[100],"We":[101],"further":[102],"two":[104],"algorithms":[107],"that":[108,127],"computationally":[109],"defined":[112],"metric.":[113],"Experimental":[114],"results":[115],"two-month":[118],"log":[120],"from":[121],"major":[123],"e-Commerce":[124],"show":[126],"our":[128],"proposed":[129],"method":[130],"can":[131],"significantly":[132],"outperform":[133],"baseline.":[134]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}