{"id":"https://openalex.org/W1979152732","doi":"https://doi.org/10.1145/2783258.2783360","title":"Discovering Valuable items from Massive Data","display_name":"Discovering Valuable items from Massive Data","publication_year":2015,"publication_date":"2015-08-07","ids":{"openalex":"https://openalex.org/W1979152732","doi":"https://doi.org/10.1145/2783258.2783360","mag":"1979152732"},"language":"en","primary_location":{"id":"doi:10.1145/2783258.2783360","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2783258.2783360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","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/A5061849953","display_name":"Hastagiri P. Vanchinathan","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Hastagiri P. Vanchinathan","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005121888","display_name":"Andreas Marfurt","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Andreas Marfurt","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039450720","display_name":"Charles-Antoine Robelin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152932","display_name":"Amadeus (Spain)","ror":"https://ror.org/04nxxn125","country_code":"ES","type":"company","lineage":["https://openalex.org/I4210152932"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Charles-Antoine Robelin","raw_affiliation_strings":["Amadeus IT group SA, Nice, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amadeus IT group SA, Nice, France","institution_ids":["https://openalex.org/I4210152932"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111504785","display_name":"Donald Kossmann","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Donald Kossmann","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003040843","display_name":"Andreas Krause","orcid":"https://orcid.org/0000-0001-7260-9673"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Andreas Krause","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1168,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.93624777,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1195","last_page":"1204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9980000257492065,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9977999925613403,"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/submodular-set-function","display_name":"Submodular set function","score":0.7966822385787964},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7181258797645569},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.587378978729248},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5674722194671631},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.562943696975708},{"id":"https://openalex.org/keywords/commit","display_name":"Commit","score":0.5136715769767761},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.49464675784111023},{"id":"https://openalex.org/keywords/knapsack-problem","display_name":"Knapsack problem","score":0.4826434254646301},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4409509301185608},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4397287964820862},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.42012208700180054},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.41006791591644287},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38437920808792114},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34915685653686523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2841492295265198},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2511213421821594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16235965490341187},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1583971083164215},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11875477433204651}],"concepts":[{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.7966822385787964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7181258797645569},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.587378978729248},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5674722194671631},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.562943696975708},{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.5136715769767761},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.49464675784111023},{"id":"https://openalex.org/C113138325","wikidata":"https://www.wikidata.org/wiki/Q864457","display_name":"Knapsack problem","level":2,"score":0.4826434254646301},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4409509301185608},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4397287964820862},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.42012208700180054},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.41006791591644287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38437920808792114},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34915685653686523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2841492295265198},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2511213421821594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16235965490341187},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1583971083164215},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11875477433204651},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2783258.2783360","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2783258.2783360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G3614962076","display_name":null,"funder_award_id":"200020_159557","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"},{"id":"https://openalex.org/G471068099","display_name":null,"funder_award_id":"307036","funder_id":"https://openalex.org/F4320334678","funder_display_name":"European Research Council"}],"funders":[{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"},{"id":"https://openalex.org/F4320334678","display_name":"European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W164706946","https://openalex.org/W1560724230","https://openalex.org/W1607035479","https://openalex.org/W1680189815","https://openalex.org/W1761637522","https://openalex.org/W1871676304","https://openalex.org/W1898824936","https://openalex.org/W1970899458","https://openalex.org/W1991169806","https://openalex.org/W2006618115","https://openalex.org/W2008098735","https://openalex.org/W2009551863","https://openalex.org/W2033810643","https://openalex.org/W2069790826","https://openalex.org/W2088577020","https://openalex.org/W2094706980","https://openalex.org/W2100549317","https://openalex.org/W2103581319","https://openalex.org/W2110005947","https://openalex.org/W2110893883","https://openalex.org/W2111241577","https://openalex.org/W2112420033","https://openalex.org/W2113922211","https://openalex.org/W2115519224","https://openalex.org/W2117353901","https://openalex.org/W2120745256","https://openalex.org/W2121671791","https://openalex.org/W2122422466","https://openalex.org/W2135414222","https://openalex.org/W2137956165","https://openalex.org/W2138779671","https://openalex.org/W2143996311","https://openalex.org/W2144933361","https://openalex.org/W2146409231","https://openalex.org/W2157442454","https://openalex.org/W2165092157","https://openalex.org/W2165618135","https://openalex.org/W2166566250","https://openalex.org/W2168405694","https://openalex.org/W2268509491","https://openalex.org/W2419658023","https://openalex.org/W2596356468","https://openalex.org/W2606098075","https://openalex.org/W2606211438","https://openalex.org/W2616052791","https://openalex.org/W2616619952","https://openalex.org/W2914331073","https://openalex.org/W2952562730","https://openalex.org/W2978329087","https://openalex.org/W2990138404","https://openalex.org/W3103014337","https://openalex.org/W3118655244","https://openalex.org/W3124229194","https://openalex.org/W4254287404","https://openalex.org/W4285719527","https://openalex.org/W4295847265","https://openalex.org/W6645091478","https://openalex.org/W6675735773","https://openalex.org/W6677973377","https://openalex.org/W6678178185","https://openalex.org/W6679881815","https://openalex.org/W6682971512","https://openalex.org/W6759166333","https://openalex.org/W6991122698"],"related_works":["https://openalex.org/W241127407","https://openalex.org/W2381035939","https://openalex.org/W1521824362","https://openalex.org/W2468477307","https://openalex.org/W2168163332","https://openalex.org/W2910645127","https://openalex.org/W162895179","https://openalex.org/W3177799343","https://openalex.org/W3119198325","https://openalex.org/W623642078"],"abstract_inverted_index":{"Suppose":[0],"there":[1],"is":[2,18],"a":[3,28,42,78,190,195,209,218],"large":[4],"collection":[5],"of":[6,34,44,93,99,147,155,175,185,192],"items,":[7,37,75],"each":[8],"with":[9],"an":[10,14,65,127,153],"associated":[11],"cost":[12,33],"and":[13,59,95,116,177,213],"inherent":[15],"utility":[16,115],"that":[17,111,132],"revealed":[19],"only":[20],"once":[21],"we":[22,40,143],"commit":[23],"to":[24,86,105,108,151,158,166,180,225],"selecting":[25,139],"it.":[26],"Given":[27],"budget":[29],"on":[30,172],"the":[31,35,60,90,134,145,148,173,200],"cumulative":[32],"selected":[36],"how":[38],"can":[39,123],"pick":[41],"subset":[43],"maximal":[45],"value?":[46],"This":[47],"task":[48,212],"generalizes":[49],"several":[50],"important":[51],"problems":[52],"such":[53],"as":[54,77,126],"multi-arm":[55],"bandits,":[56],"active":[57],"search":[58],"knapsack":[61],"problem.":[62],"We":[63,102,168],"present":[64],"algorithm,":[66],"GP-SELECT,":[67],"which":[68],"utilizes":[69],"prior":[70],"knowledge":[71],"about":[72],"similarity":[73],"between":[74],"expressed":[76],"kernel":[79],"function.":[80],"GP-SELECT":[81,104,176],"uses":[82],"Gaussian":[83],"process":[84],"prediction":[85],"balance":[87],"exploration":[88],"(estimating":[89],"unknown":[91],"value":[92],"items)":[94],"exploitation":[96],"(selecting":[97],"items":[98,224],"high":[100,114],"value).":[101],"extend":[103],"be":[106,124],"able":[107],"discover":[109],"sets":[110],"simultaneously":[112],"have":[113],"are":[117],"diverse.":[118],"Our":[119],"preference":[120],"for":[121,199],"diversity":[122],"specified":[125],"arbitrary":[128],"monotone":[129],"submodular":[130],"function":[131],"quantifies":[133],"diminishing":[135],"returns":[136],"obtained":[137],"when":[138],"similar":[140],"items.":[141],"Furthermore,":[142],"exploit":[144],"structure":[146],"model":[149],"updates":[150],"achieve":[152],"order":[154],"magnitude":[156],"(up":[157],"40X)":[159],"speedup":[160],"in":[161,194,208,217],"our":[162],"experiments":[163],"without":[164],"resorting":[165],"approximations.":[167],"provide":[169],"strong":[170],"guarantees":[171],"performance":[174],"apply":[178],"it":[179],"three":[181],"real-world":[182],"case":[183],"studies":[184],"industrial":[186],"relevance:":[187],"(1)":[188],"Refreshing":[189],"repository":[191],"prices":[193],"Global":[196],"Distribution":[197],"System":[198],"travel":[201],"industry,":[202],"(2)":[203],"Identifying":[204],"diverse,":[205],"binding-affine":[206],"peptides":[207],"vaccine":[210],"design":[211],"(3)":[214],"Maximizing":[215],"clicks":[216],"web-scale":[219],"recommender":[220],"system":[221],"by":[222],"recommending":[223],"users.":[226]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}