{"id":"https://openalex.org/W4385567901","doi":"https://doi.org/10.1145/3580305.3599909","title":"Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem","display_name":"Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385567901","doi":"https://doi.org/10.1145/3580305.3599909"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599909","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599909","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599909","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599909","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100370777","display_name":"Jiayi Liu","orcid":"https://orcid.org/0009-0009-8014-4218"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiayi Liu","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010290944","display_name":"J. Neville","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Neville","raw_affiliation_strings":["Purdue University &amp; Microsoft Research, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University &amp; Microsoft Research, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100370777"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":1.1035,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.87062226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4527","last_page":"4538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12607","display_name":"Personal Information Management and User Behavior","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12607","display_name":"Personal Information Management and User Behavior","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9825000166893005,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9822999835014343,"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/computer-science","display_name":"Computer science","score":0.8240171670913696},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6683188080787659},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.627669095993042},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5697028040885925},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5473648309707642},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5311509370803833},{"id":"https://openalex.org/keywords/communication-source","display_name":"Communication source","score":0.4630790650844574},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.423267126083374}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8240171670913696},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6683188080787659},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.627669095993042},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5697028040885925},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5473648309707642},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5311509370803833},{"id":"https://openalex.org/C198104137","wikidata":"https://www.wikidata.org/wiki/Q974688","display_name":"Communication source","level":2,"score":0.4630790650844574},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.423267126083374},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3580305.3599909","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599909","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599909","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2308.08460","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.08460","pdf_url":"https://arxiv.org/pdf/2308.08460","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3580305.3599909","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599909","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599909","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385567901.pdf","grobid_xml":"https://content.openalex.org/works/W4385567901.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1492920282","https://openalex.org/W1603920809","https://openalex.org/W1852383912","https://openalex.org/W1968535060","https://openalex.org/W2038808545","https://openalex.org/W2050042708","https://openalex.org/W2060907774","https://openalex.org/W2076279155","https://openalex.org/W2076428443","https://openalex.org/W2110028669","https://openalex.org/W2111367974","https://openalex.org/W2121702730","https://openalex.org/W2131689821","https://openalex.org/W2136522026","https://openalex.org/W2137891816","https://openalex.org/W2270188535","https://openalex.org/W2312920711","https://openalex.org/W2614403482","https://openalex.org/W2901597048","https://openalex.org/W2949639089","https://openalex.org/W2984138497","https://openalex.org/W3016356276","https://openalex.org/W3092386655","https://openalex.org/W3094145610","https://openalex.org/W3123289716","https://openalex.org/W3126884874","https://openalex.org/W3154449962","https://openalex.org/W3209698437","https://openalex.org/W4229075504","https://openalex.org/W4229604467","https://openalex.org/W4248774759","https://openalex.org/W4285324686"],"related_works":["https://openalex.org/W2156910174","https://openalex.org/W1995054232","https://openalex.org/W2011510925","https://openalex.org/W1557920161","https://openalex.org/W1556709767","https://openalex.org/W1993023208","https://openalex.org/W4291020658","https://openalex.org/W2593813644","https://openalex.org/W2061476331","https://openalex.org/W2151215270"],"abstract_inverted_index":{"Email":[0,85],"platforms":[1],"need":[2],"to":[3,37,69,76,155],"generate":[4],"personalized":[5],"rankings":[6,144],"of":[7,90],"emails":[8],"that":[9,63,102,131,140,160],"satisfy":[10],"user":[11,166],"preferences,":[12,110],"which":[13],"may":[14],"vary":[15],"over":[16,119],"time.":[17,120],"We":[18,53,79,121],"approach":[19],"this":[20],"as":[21],"a":[22,59,87,127],"recommendation":[23],"problem":[24],"based":[25],"on":[26,82,126],"three":[27],"criteria:":[28],"closeness":[29],"(how":[30,41,48],"relevant":[31],"the":[32,38,43,50,83],"sender":[33],"and":[34,46,74,93,138],"topic":[35],"are":[36],"user),":[39],"timeliness":[40],"recent":[42],"email":[44,51,136,157],"is),":[45],"conciseness":[47],"brief":[49],"is).":[52],"propose":[54],"MOSR":[55,81,103],"(Multi-Objective":[56],"Stationary":[57],"Recommender),":[58],"novel":[60,151],"online":[61],"algorithm":[62],"uses":[64],"an":[65],"adaptive":[66],"control":[67],"model":[68],"dynamically":[70],"balance":[71],"these":[72],"criteria":[73,115],"adapt":[75],"preference":[77],"changes.":[78],"evaluate":[80],"Enron":[84],"Dataset,":[86],"large":[88],"collection":[89],"real":[91],"emails,":[92],"compare":[94],"it":[95,141],"with":[96],"other":[97],"baselines.":[98],"The":[99],"results":[100],"show":[101,139],"achieves":[104],"better":[105],"performance,":[106],"especially":[107],"under":[108],"non-stationary":[109],"where":[111],"users":[112],"value":[113],"different":[114,146],"more":[116],"or":[117],"less":[118],"also":[122],"test":[123],"MOSR's":[124],"robustness":[125],"smaller":[128],"down-sampled":[129],"dataset":[130],"exhibits":[132],"high":[133],"variance":[134],"in":[135],"characteristics,":[137],"maintains":[142],"stable":[143],"across":[145],"samples.":[147],"Our":[148],"work":[149],"offers":[150],"insights":[152],"into":[153],"how":[154],"design":[156],"re-ranking":[158],"systems":[159],"account":[161],"for":[162],"multiple":[163],"objectives":[164],"impacting":[165],"satisfaction.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
