{"id":"https://openalex.org/W2986211972","doi":"https://doi.org/10.1145/3357384.3358115","title":"Faster Algorithms for <i>k</i> -Regret Minimizing Sets via Monotonicity and Sampling","display_name":"Faster Algorithms for <i>k</i> -Regret Minimizing Sets via Monotonicity and Sampling","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2986211972","doi":"https://doi.org/10.1145/3357384.3358115","mag":"2986211972"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3358115","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3358115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","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/A5023251393","display_name":"Qi Dong","orcid":"https://orcid.org/0000-0002-7302-5706"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Dong","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046551456","display_name":"Jiping Zheng","orcid":"https://orcid.org/0000-0003-4378-5250"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiping Zheng","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023251393"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.6634,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69639131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2213","last_page":"2216"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"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":0.9998999834060669,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.978600025177002,"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/regret","display_name":"Regret","score":0.9614022970199585},{"id":"https://openalex.org/keywords/skyline","display_name":"Skyline","score":0.8038110733032227},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.7802479267120361},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.6988886594772339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6439131498336792},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5546530485153198},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4985804557800293},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.480352520942688},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47140267491340637},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.46125707030296326},{"id":"https://openalex.org/keywords/efficient-algorithm","display_name":"Efficient algorithm","score":0.41730231046676636},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38105422258377075},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32865190505981445},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2861441373825073},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10247603058815002}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.9614022970199585},{"id":"https://openalex.org/C2780757406","wikidata":"https://www.wikidata.org/wiki/Q465837","display_name":"Skyline","level":2,"score":0.8038110733032227},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.7802479267120361},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.6988886594772339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6439131498336792},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5546530485153198},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4985804557800293},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.480352520942688},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47140267491340637},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.46125707030296326},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.41730231046676636},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38105422258377075},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32865190505981445},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2861441373825073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10247603058815002},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357384.3358115","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3358115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W79208629","https://openalex.org/W800095131","https://openalex.org/W1998952728","https://openalex.org/W2004796840","https://openalex.org/W2009688537","https://openalex.org/W2146831356","https://openalex.org/W2170188482","https://openalex.org/W2290570034","https://openalex.org/W2594880695","https://openalex.org/W2888613844","https://openalex.org/W2897961923","https://openalex.org/W3125176478"],"related_works":["https://openalex.org/W1994126304","https://openalex.org/W2087306197","https://openalex.org/W2971351794","https://openalex.org/W1973297295","https://openalex.org/W4376155396","https://openalex.org/W2316530548","https://openalex.org/W2505069962","https://openalex.org/W3096764880","https://openalex.org/W3177158450","https://openalex.org/W2107674253"],"abstract_inverted_index":{"Regret-based":[0],"queries":[1,9,29,87],"are":[2,30,71],"a":[3,20,81],"complement":[4],"of":[5,23,92,105],"top-k":[6],"and":[7,52,74,109,113],"skyline":[8],"when":[10],"users":[11],"cannot":[12],"specify":[13],"accurate":[14],"utility":[15],"functions":[16],"while":[17],"must":[18],"output":[19],"controllable":[21],"size":[22],"the":[24,50,54,90,93,102],"query":[25,44],"results.":[26],"Various":[27],"regret-based":[28],"proposed":[31,118],"in":[32],"last":[33],"decade":[34],"for":[35,85],"multi-criteria":[36],"decision":[37],"making.":[38],"The":[39],"k-regret":[40,56,68],"minimizing":[41,69],"set":[42],"(k-RMS)":[43],"which":[45],"returns":[46],"r":[47],"points":[48],"from":[49],"dataset":[51],"minimizes":[53],"maximum":[55],"ratio":[57,95],"has":[58],"been":[59],"extensively":[60],"studied.":[61],"However,":[62],"existing":[63,123],"state-of-art":[64,124],"algorithms":[65],"to":[66,122],"find":[67],"sets":[70],"very":[72],"time-consuming":[73],"unapplicable.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79],"propose":[80],"faster":[82],"algorithm":[83,108,119],"SAMPGREED":[84,107],"k-RMS":[86],"by":[88],"utilizing":[89],"monotonicity":[91],"regret":[94],"function":[96],"with":[97],"sampling":[98],"techniques.":[99],"We":[100],"provide":[101],"theoretical":[103],"analysis":[104],"our":[106,117],"experiments":[110],"on":[111],"synthetic":[112],"real":[114],"datasets":[115],"verify":[116],"is":[120],"superior":[121],"approaches.":[125]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
