{"id":"https://openalex.org/W4402042488","doi":"https://doi.org/10.14778/3681954.3681993","title":"A Sampling-Based Framework for Hypothesis Testing on Large Attributed Graphs","display_name":"A Sampling-Based Framework for Hypothesis Testing on Large Attributed Graphs","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4402042488","doi":"https://doi.org/10.14778/3681954.3681993"},"language":"en","primary_location":{"id":"doi:10.14778/3681954.3681993","is_oa":false,"landing_page_url":"http://dx.doi.org/10.14778/3681954.3681993","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/A5100377649","display_name":"Yun Wang","orcid":"https://orcid.org/0000-0002-9858-2066"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I4210142478","display_name":"HKU-Pasteur Research Pole","ror":"https://ror.org/03wwjjr94","country_code":"HK","type":"facility","lineage":["https://openalex.org/I4210142478"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yun Wang","raw_affiliation_strings":["The University of Hong Kong","HKU - The University of Hong Kong (Pokfulam, Hong Kong - Hong Kong SAR China)"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"HKU - The University of Hong Kong (Pokfulam, Hong Kong - Hong Kong SAR China)","institution_ids":["https://openalex.org/I4210142478","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080325696","display_name":"Chrysanthi Kosyfaki","orcid":"https://orcid.org/0000-0002-0920-1437"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I4210142478","display_name":"HKU-Pasteur Research Pole","ror":"https://ror.org/03wwjjr94","country_code":"HK","type":"facility","lineage":["https://openalex.org/I4210142478"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Chrysanthi Kosyfaki","raw_affiliation_strings":["The University of Hong Kong","HKU - The University of Hong Kong (Pokfulam, Hong Kong - Hong Kong SAR China)"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"HKU - The University of Hong Kong (Pokfulam, Hong Kong - Hong Kong SAR China)","institution_ids":["https://openalex.org/I4210142478","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081664259","display_name":"Sihem Amer-Yahia","orcid":"https://orcid.org/0000-0002-6194-4502"},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sihem Amer-Yahia","raw_affiliation_strings":["CNRS, Univ. Grenoble Aples","CNRS - Centre National de la Recherche Scientifique (France)"],"affiliations":[{"raw_affiliation_string":"CNRS, Univ. Grenoble Aples","institution_ids":["https://openalex.org/I899635006","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"CNRS - Centre National de la Recherche Scientifique (France)","institution_ids":["https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005847882","display_name":"Reynold Cheng","orcid":"https://orcid.org/0000-0002-9480-9809"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I4210142478","display_name":"HKU-Pasteur Research Pole","ror":"https://ror.org/03wwjjr94","country_code":"HK","type":"facility","lineage":["https://openalex.org/I4210142478"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Reynold Cheng","raw_affiliation_strings":["The University of Hong Kong","HKU - The University of Hong Kong (Pokfulam, Hong Kong - Hong Kong SAR China)"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"HKU - The University of Hong Kong (Pokfulam, Hong Kong - Hong Kong SAR China)","institution_ids":["https://openalex.org/I4210142478","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100377649"],"corresponding_institution_ids":["https://openalex.org/I4210142478","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13582759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"11","first_page":"3192","last_page":"3200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9941999912261963,"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/T11719","display_name":"Data Quality and Management","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.690176248550415},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6662659049034119},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.6585766077041626},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5752301216125488},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4837675094604492},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.475344181060791},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.46344876289367676},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4186203181743622},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34122806787490845},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3335449993610382},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.28224682807922363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2598339021205902}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.690176248550415},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6662659049034119},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.6585766077041626},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5752301216125488},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4837675094604492},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.475344181060791},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.46344876289367676},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4186203181743622},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34122806787490845},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3335449993610382},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.28224682807922363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2598339021205902},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3681954.3681993","is_oa":false,"landing_page_url":"http://dx.doi.org/10.14778/3681954.3681993","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:HAL:hal-04728226v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04728226","pdf_url":null,"source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the VLDB Endowment (PVLDB), 2024, 17 (11), pp.3192-3200. ⟨10.14778/3681954.3681993⟩","raw_type":"Journal articles"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1993688359","https://openalex.org/W2022322548","https://openalex.org/W2046360729","https://openalex.org/W2048596679","https://openalex.org/W2052685685","https://openalex.org/W2110117460","https://openalex.org/W2134724105","https://openalex.org/W2137135938","https://openalex.org/W2146008005","https://openalex.org/W2157747946","https://openalex.org/W2159009490","https://openalex.org/W2170358724","https://openalex.org/W2404258945","https://openalex.org/W2507350365","https://openalex.org/W2748846107","https://openalex.org/W2898152280","https://openalex.org/W2963191122","https://openalex.org/W2985169463","https://openalex.org/W3103445515","https://openalex.org/W4301113013"],"related_works":["https://openalex.org/W2787993192","https://openalex.org/W2158269427","https://openalex.org/W4381280689","https://openalex.org/W2847365777","https://openalex.org/W3128025644","https://openalex.org/W2355048207","https://openalex.org/W2750422482","https://openalex.org/W3125827053","https://openalex.org/W2920521957","https://openalex.org/W4214882840"],"abstract_inverted_index":{"Hypothesis":[0],"testing":[1,29,53],"is":[2,32],"a":[3,50,72],"statistical":[4],"method":[5],"used":[6],"to":[7,112],"draw":[8],"conclusions":[9],"about":[10],"populations":[11],"from":[12],"sample":[13],"data,":[14],"typically":[15],"represented":[16],"in":[17,25,87,128],"tables.":[18],"With":[19],"the":[20,84,88,107,122],"prevalence":[21],"of":[22,109,124,130],"graph":[23,60,115],"representations":[24],"real-life":[26],"applications,":[27],"hypothesis":[28,52,119],"on":[30,45,102],"graphs":[31],"gaining":[33],"importance.":[34],"In":[35],"this":[36],"work,":[37],"we":[38,69],"formalize":[39],"node,":[40],"edge,":[41],"and":[42,66,96,121,132],"path":[43],"hypotheses":[44],"attributed":[46],"graphs.":[47],"We":[48,90],"develop":[49],"sampling-based":[51],"framework,":[54],"which":[55],"can":[56],"accommodate":[57],"existing":[58],"hypothesis-agnostic":[59],"sampling":[61,116,126],"methods.":[62],"To":[63],"achieve":[64],"accurate":[65],"time-efficient":[67],"sampling,":[68],"then":[70],"propose":[71,97],"Path-Hypothesis-Aware":[73],"SamplEr,":[74],"PHASE,":[75],"an":[76],"m":[77],"-dimensional":[78],"random":[79],"walk":[80],"that":[81],"accounts":[82],"for":[83,118],"paths":[85],"specified":[86],"hypothesis.":[89],"further":[91],"optimize":[92],"its":[93],"time":[94,133],"efficiency":[95],"PHASE":[98],"opt":[99],".":[100],"Experiments":[101],"three":[103],"real":[104],"datasets":[105],"demonstrate":[106],"ability":[108],"our":[110],"framework":[111],"leverage":[113],"common":[114],"methods":[117,127],"testing,":[120],"superiority":[123],"hypothesis-aware":[125],"terms":[129],"accuracy":[131],"efficiency.":[134]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}