{"id":"https://openalex.org/W842283414","doi":"https://doi.org/10.14778/2757807.2757809","title":"An efficient similarity search framework for SimRank over large dynamic graphs","display_name":"An efficient similarity search framework for SimRank over large dynamic graphs","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W842283414","doi":"https://doi.org/10.14778/2757807.2757809","mag":"842283414"},"language":"en","primary_location":{"id":"doi:10.14778/2757807.2757809","is_oa":false,"landing_page_url":"https://doi.org/10.14778/2757807.2757809","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-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/A5014615052","display_name":"Yingxia Shao","orcid":"https://orcid.org/0000-0002-8559-2628"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingxia Shao","raw_affiliation_strings":["Peking University"],"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062357883","display_name":"Bin Cui","orcid":"https://orcid.org/0000-0003-1681-4677"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Cui","raw_affiliation_strings":["Peking University"],"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333516","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-8257-5806"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["HKUST"],"affiliations":[{"raw_affiliation_string":"HKUST","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448080","display_name":"Mingming Liu","orcid":"https://orcid.org/0000-0002-9348-8994"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingming Liu","raw_affiliation_strings":["Peking University"],"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"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"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Microsoft Research","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5014615052"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":4.7717,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.95117885,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"8","issue":"8","first_page":"838","last_page":"849"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9947999715805054,"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":0.9947999715805054,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9923999905586243,"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/T11106","display_name":"Data Management and Algorithms","score":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6463409662246704},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.48970988392829895},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.4894465506076813},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4825798571109772},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.477192759513855},{"id":"https://openalex.org/keywords/chordal-graph","display_name":"Chordal graph","score":0.4540849030017853},{"id":"https://openalex.org/keywords/maximal-independent-set","display_name":"Maximal independent set","score":0.4458773136138916},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4410002827644348},{"id":"https://openalex.org/keywords/random-graph","display_name":"Random graph","score":0.41867533326148987},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.41373321413993835},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3707560896873474},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3665095865726471},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2476809322834015},{"id":"https://openalex.org/keywords/1-planar-graph","display_name":"1-planar graph","score":0.1995011866092682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6463409662246704},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.48970988392829895},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.4894465506076813},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4825798571109772},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.477192759513855},{"id":"https://openalex.org/C160446614","wikidata":"https://www.wikidata.org/wiki/Q1322892","display_name":"Chordal graph","level":3,"score":0.4540849030017853},{"id":"https://openalex.org/C18359143","wikidata":"https://www.wikidata.org/wiki/Q7888149","display_name":"Maximal independent set","level":5,"score":0.4458773136138916},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4410002827644348},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.41867533326148987},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.41373321413993835},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3707560896873474},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3665095865726471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2476809322834015},{"id":"https://openalex.org/C102192266","wikidata":"https://www.wikidata.org/wiki/Q4545823","display_name":"1-planar graph","level":4,"score":0.1995011866092682},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/2757807.2757809","is_oa":false,"landing_page_url":"https://doi.org/10.14778/2757807.2757809","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-78396","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-78396","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W130710483","https://openalex.org/W1545879303","https://openalex.org/W1558967143","https://openalex.org/W1564491517","https://openalex.org/W1594224465","https://openalex.org/W1600053460","https://openalex.org/W1738124305","https://openalex.org/W1995973731","https://openalex.org/W1996849720","https://openalex.org/W2000893191","https://openalex.org/W2021758280","https://openalex.org/W2023210016","https://openalex.org/W2057169561","https://openalex.org/W2063131624","https://openalex.org/W2070109133","https://openalex.org/W2072501842","https://openalex.org/W2083257370","https://openalex.org/W2095121807","https://openalex.org/W2103012681","https://openalex.org/W2103243299","https://openalex.org/W2117831564","https://openalex.org/W2130854091","https://openalex.org/W2146008005","https://openalex.org/W2156543375","https://openalex.org/W2159732209","https://openalex.org/W2163668090","https://openalex.org/W2568082647","https://openalex.org/W2752885492","https://openalex.org/W3000082853","https://openalex.org/W3111526966","https://openalex.org/W4238472918","https://openalex.org/W4300579247","https://openalex.org/W7029321148"],"related_works":["https://openalex.org/W4283803822","https://openalex.org/W2029336174","https://openalex.org/W2527172197","https://openalex.org/W2963009577","https://openalex.org/W2063494850","https://openalex.org/W2788975631","https://openalex.org/W3199257895","https://openalex.org/W2903402681","https://openalex.org/W4225525972","https://openalex.org/W1994963913"],"abstract_inverted_index":{"SimRank":[0,19,197],"is":[1,20,130,138,159,207,234],"an":[2,21],"important":[3,22],"measure":[4],"of":[5,12,62,68,107,133,141,184,205,218],"vertex-pair":[6],"similarity":[7,15,56,73,93],"according":[8],"to":[9,110,162,214],"the":[10,43,100,131,139,154,166,182,196,203,216,220,229,232],"structure":[11],"graphs.":[13,78,143,164,186],"The":[14,52,144],"search":[16,57,74,94,171],"based":[17,180],"on":[18,181,228],"operation":[23],"for":[24,55,91],"identifying":[25],"similar":[26,172],"vertices":[27,134,173,179],"in":[28,35,42,60,115,151],"a":[29,84,105,116],"graph":[30,146,155],"and":[31,49,64,126,135],"has":[32],"been":[33],"employed":[34],"many":[36],"data":[37],"analysis":[38],"applications.":[39],"Nowadays,":[40],"graphs":[41,109,222,246],"real":[44],"world":[45],"become":[46],"much":[47],"larger":[48],"more":[50],"dynamic.":[51],"existing":[53],"solutions":[54],"are":[58],"expensive":[59],"terms":[61],"time":[63,125],"space":[65],"cost.":[66],"None":[67],"them":[69],"can":[70,147,170,194,223,242],"efficiently":[71,149],"support":[72],"over":[75],"large":[76],"dynamic":[77,163,244],"In":[79,99],"this":[80],"paper,":[81],"we":[82],"propose":[83],"novel":[85,117],"two-stage":[86],"random-walk":[87],"sampling":[88],"framework":[89],"(TSF)":[90],"SimRank-based":[92],"(e.g.,":[95],"top-":[96],"k":[97],"search).":[98],"preprocessing":[101],"stage,":[102,168],"TSF":[103,158,169,193,241],"samples":[104],"set":[106],"one-way":[108,142,145,185,221],"index":[111],"raw":[112],"random":[113],"walks":[114],"manner":[118],"within":[119],"O":[120],"(":[121],"NR":[122],"g":[123,137],")":[124],"space,":[127],"where":[128],"N":[129],"number":[132,140],"R":[136,190],"be":[148,225],"updated":[150],"accordance":[152],"with":[153,188,199,247],"modification,":[156],"thus":[157],"well":[160],"suited":[161],"During":[165],"query":[167],"fast":[174],"by":[175,209],"naturally":[176],"pruning":[177],"unqualified":[178],"connectivity":[183],"Furthermore,":[187],"additional":[189],"q":[191],"samples,":[192],"estimate":[195],"score":[198],"probability":[200],"[EQUATION]":[201],"if":[202],"error":[204],"approximation":[206],"bounded":[208],"1":[210],"--":[211],"\u03b5.":[212],"Finally,":[213],"guarantee":[215],"scalability":[217],"TSF,":[219],"also":[224],"compactly":[226],"stored":[227],"disk":[230],"when":[231],"memory":[233],"limited.":[235],"Extensive":[236],"experiments":[237],"have":[238],"demonstrated":[239],"that":[240],"handle":[243],"billion-edge":[245],"high":[248],"performance.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3}],"updated_date":"2026-02-25T23:00:34.991745","created_date":"2025-10-10T00:00:00"}
