{"id":"https://openalex.org/W4413973338","doi":"https://doi.org/10.14778/3746405.3746428","title":"Path-Centric Cardinality Estimation for Subgraph Matching","display_name":"Path-Centric Cardinality Estimation for Subgraph Matching","publication_year":2025,"publication_date":"2025-05-01","ids":{"openalex":"https://openalex.org/W4413973338","doi":"https://doi.org/10.14778/3746405.3746428"},"language":"en","primary_location":{"id":"doi:10.14778/3746405.3746428","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3746405.3746428","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/A5026852887","display_name":"Zhengdong Wang","orcid":"https://orcid.org/0000-0002-0435-1057"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengdong Wang","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035018298","display_name":"Qiang Yin","orcid":"https://orcid.org/0000-0003-3398-8345"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Yin","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103178004","display_name":"Longbin Lai","orcid":"https://orcid.org/0009-0009-4735-3835"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Longbin Lai","raw_affiliation_strings":["Alibaba Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group","institution_ids":["https://openalex.org/I4210095624"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7655,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74591276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"18","issue":"9","first_page":"3063","last_page":"3076"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965999722480774,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/path","display_name":"Path (computing)","score":0.6831389665603638},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.6545047163963318},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6074846386909485},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.48395445942878723},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.45786479115486145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4539506137371063},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3789137005805969},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3661000728607178},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3370884358882904},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3014570474624634},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.26259249448776245},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.16086232662200928},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12859496474266052},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11458510160446167},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10567063093185425},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.0656021237373352}],"concepts":[{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.6831389665603638},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.6545047163963318},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6074846386909485},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.48395445942878723},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.45786479115486145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4539506137371063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3789137005805969},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3661000728607178},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3370884358882904},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3014570474624634},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.26259249448776245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.16086232662200928},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12859496474266052},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11458510160446167},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10567063093185425},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.0656021237373352},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3746405.3746428","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3746405.3746428","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1516019649","https://openalex.org/W1973346610","https://openalex.org/W1977041160","https://openalex.org/W2010890196","https://openalex.org/W2080234606","https://openalex.org/W2100387739","https://openalex.org/W2132823934","https://openalex.org/W2140840007","https://openalex.org/W2144982963","https://openalex.org/W2146492010","https://openalex.org/W2243803726","https://openalex.org/W2396309311","https://openalex.org/W2421547754","https://openalex.org/W2585424461","https://openalex.org/W2755385361","https://openalex.org/W2798499404","https://openalex.org/W2798875768","https://openalex.org/W2799059383","https://openalex.org/W2950833175","https://openalex.org/W2963467900","https://openalex.org/W3030639942","https://openalex.org/W3030994385","https://openalex.org/W3111141572","https://openalex.org/W3161742868","https://openalex.org/W3176186668","https://openalex.org/W3176395835","https://openalex.org/W3190216043","https://openalex.org/W4206064074","https://openalex.org/W4206830372","https://openalex.org/W4226086155","https://openalex.org/W4242142158","https://openalex.org/W4281666535","https://openalex.org/W4285338532","https://openalex.org/W4289706945","https://openalex.org/W4366502978","https://openalex.org/W4380433098","https://openalex.org/W4380433194","https://openalex.org/W4393183879","https://openalex.org/W4401657016","https://openalex.org/W4405623369","https://openalex.org/W4408060237","https://openalex.org/W4409219074","https://openalex.org/W4411374285"],"related_works":["https://openalex.org/W2002177687","https://openalex.org/W2058438338","https://openalex.org/W2019471580","https://openalex.org/W2941284322","https://openalex.org/W4224920876","https://openalex.org/W2168299207","https://openalex.org/W4308671316","https://openalex.org/W2950751300","https://openalex.org/W4301272096","https://openalex.org/W2371352078"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"PathCE,":[3],"a":[4,27,44,52,58,63,73,85,132],"path-centric":[5,33],"cardinality":[6,99,122],"estimation":[7,14,108,168],"framework":[8],"for":[9,67,139],"subgraph":[10],"matching.":[11],"PathCE":[12,69,96,162],"improves":[13],"accuracy":[15],"by":[16],"utilizing":[17],"statistics":[18,42,91],"from":[19,43],"short":[20,39],"graph":[21,35,46,54,59,65,142],"queries.":[22],"At":[23],"its":[24],"core":[25],"is":[26],"novel":[28],"data":[29,45],"structure":[30],"called":[31],"the":[32,98,113,120,149],"summary":[34,171],"(PSG),":[36],"which":[37],"captures":[38],"path":[40],"query":[41,60,75,87],"G":[47,55,66,76,82,94,101,103,126],"and":[48,62,102,157,170],"represents":[49],"them":[50],"in":[51,81,88,93,143,166],"new":[53],".":[56,95],"Given":[57],"Q":[61,71,89,124],"PSG":[64],"G,":[68],"decomposes":[70],"into":[72],"simpler":[74],",":[77,104],"where":[78],"each":[79],"edge":[80],"corresponds":[83],"to":[84],"sub-path":[86],"with":[90,148],"included":[92],"estimates":[97],"using":[100],"requiring":[105],"significantly":[106],"fewer":[107],"iterations":[109],"while":[110],"ensuring":[111],"that":[112,136,161],"estimate":[114],"remains":[115],"an":[116],"upper":[117],"bound":[118],"on":[119,155],"true":[121],"of":[123,151],"(":[125],").":[127],"It":[128],"also":[129],"includes":[130],"PSGBuilder,":[131],"parallelly":[133],"scalable":[134],"algorithm":[135],"constructs":[137],"PSG's":[138],"any":[140],"given":[141],"linear":[144],"time,":[145],"efficiently":[146],"scaling":[147],"number":[150],"processors.":[152],"Empirical":[153],"results":[154],"real-world":[156],"synthetic":[158],"datasets":[159],"show":[160],"outperforms":[163],"state-of-the-art":[164],"baselines":[165],"accuracy,":[167],"latency,":[169],"construction":[172],"efficiency.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
