{"id":"https://openalex.org/W2083970694","doi":"https://doi.org/10.1145/2684822.2685310","title":"Inverting a Steady-State","display_name":"Inverting a Steady-State","publication_year":2015,"publication_date":"2015-01-28","ids":{"openalex":"https://openalex.org/W2083970694","doi":"https://doi.org/10.1145/2684822.2685310","mag":"2083970694"},"language":"en","primary_location":{"id":"doi:10.1145/2684822.2685310","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2684822.2685310","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2685310&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2685310&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101772779","display_name":"Ravi Kumar","orcid":"https://orcid.org/0000-0002-2203-2586"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ravi Kumar","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068021191","display_name":"Andrew Tomkins","orcid":"https://orcid.org/0000-0002-1611-9255"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Tomkins","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070795618","display_name":"Sergei Vassilvitskii","orcid":"https://orcid.org/0000-0003-0235-1624"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergei Vassilvitskii","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049077665","display_name":"Erik Vee","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erik Vee","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101772779"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":2.1425,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.87162752,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"359","last_page":"368"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10742","display_name":"Peer-to-Peer Network Technologies","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.6618328094482422},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6536237001419067},{"id":"https://openalex.org/keywords/stochastic-matrix","display_name":"Stochastic matrix","score":0.5970059633255005},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5888547301292419},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5458888411521912},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.539945662021637},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5042897462844849},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49813079833984375},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4953962564468384},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.43533575534820557},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42996829748153687},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4288775324821472},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.42159390449523926},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38243263959884644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29797202348709106},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12807399034500122}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6618328094482422},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6536237001419067},{"id":"https://openalex.org/C49555168","wikidata":"https://www.wikidata.org/wiki/Q176583","display_name":"Stochastic matrix","level":3,"score":0.5970059633255005},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5888547301292419},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5458888411521912},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.539945662021637},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5042897462844849},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49813079833984375},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4953962564468384},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.43533575534820557},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42996829748153687},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4288775324821472},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.42159390449523926},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38243263959884644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29797202348709106},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12807399034500122},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2684822.2685310","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2684822.2685310","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2685310&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.682.248","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://theory.stanford.edu/%7Esergei/papers/wsdm15-cset.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/2684822.2685310","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2684822.2685310","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2685310&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2083970694.pdf","grobid_xml":"https://content.openalex.org/works/W2083970694.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W65714572","https://openalex.org/W223708877","https://openalex.org/W565204528","https://openalex.org/W1600293573","https://openalex.org/W1854214752","https://openalex.org/W1906178366","https://openalex.org/W1959086707","https://openalex.org/W1964579932","https://openalex.org/W1975914563","https://openalex.org/W1979258712","https://openalex.org/W1987717935","https://openalex.org/W2014478203","https://openalex.org/W2036120890","https://openalex.org/W2056760934","https://openalex.org/W2063292248","https://openalex.org/W2066636486","https://openalex.org/W2074270446","https://openalex.org/W2094536313","https://openalex.org/W2096487091","https://openalex.org/W2108207895","https://openalex.org/W2108272874","https://openalex.org/W2111289574","https://openalex.org/W2121808626","https://openalex.org/W2125493559","https://openalex.org/W2134711723","https://openalex.org/W2138309709","https://openalex.org/W2138621811","https://openalex.org/W2139146018","https://openalex.org/W2140350208","https://openalex.org/W2141075029","https://openalex.org/W2143917438","https://openalex.org/W2161118554","https://openalex.org/W2170344111","https://openalex.org/W3015812362","https://openalex.org/W3120740533","https://openalex.org/W3152367353","https://openalex.org/W6639055396","https://openalex.org/W6639758573","https://openalex.org/W6655271531","https://openalex.org/W6673974147","https://openalex.org/W6675974083","https://openalex.org/W7046063147"],"related_works":["https://openalex.org/W2734729804","https://openalex.org/W2015136492","https://openalex.org/W1968612088","https://openalex.org/W2186430569","https://openalex.org/W2364963676","https://openalex.org/W3041997070","https://openalex.org/W2735388074","https://openalex.org/W4388292488","https://openalex.org/W2351194865","https://openalex.org/W2756643213"],"abstract_inverted_index":{"We":[0,22,55,96,153],"consider":[1],"the":[2,16,28,80,87,92,108,120,127,145,173,178],"problem":[3,29,103,132],"of":[4,19,32,72,82,119,138,190],"inferring":[5,33],"choices":[6,180],"made":[7],"by":[8],"users":[9],"based":[10],"only":[11],"on":[12,52],"aggregate":[13],"data":[14,175],"containing":[15],"relative":[17],"popularity":[18],"each":[20,83],"item.":[21],"propose":[23],"a":[24,34,38,45,48,59,65,69,112,116,135,188],"framework":[25,157],"that":[26,31,86,144,166],"models":[27],"as":[30],"Markov":[35],"chain":[36],"given":[37,44],"stationary":[39],"distribution.":[40],"Formally,":[41],"we":[42,142],"are":[43,56],"graph":[46],"and":[47,133,164,176],"target":[49],"steady-state":[50],"distribution":[51],"its":[53],"nodes.":[54],"also":[57],"give":[58],"mapping":[60],"from":[61,68],"per-node":[62],"scores":[63,81],"to":[64,78,130,158,171],"transition":[66,89],"matrix,":[67],"broad":[70],"family":[71],"such":[73,85],"mappings.":[74],"The":[75],"goal":[76],"is":[77,104,169],"set":[79],"node":[84],"resulting":[88],"matrix":[90],"induces":[91],"desired":[93],"steady":[94],"state.":[95],"prove":[97],"sufficient":[98],"conditions":[99],"under":[100],"which":[101],"this":[102,131,156],"feasible":[105,109],"and,":[106],"for":[107,115],"instances,":[110],"obtain":[111],"simple":[113],"algorithm":[114,124,146,168],"generic":[117],"version":[118],"problem.":[121],"This":[122],"iterative":[123],"provably":[125],"finds":[126],"unique":[128],"solution":[129],"has":[134],"polynomial":[136],"rate":[137],"convergence;":[139],"in":[140,161],"practice":[141],"find":[143],"converges":[147],"after":[148],"fewer":[149],"than":[150,183],"ten":[151],"iterations.":[152],"then":[154],"apply":[155],"choice":[159],"problems":[160],"online":[162],"settings":[163],"show":[165],"our":[167],"able":[170],"explain":[172],"observed":[174],"predict":[177],"user":[179],"much":[181],"better":[182],"other":[184],"competing":[185],"baselines":[186],"across":[187],"variety":[189],"diverse":[191],"datasets.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}