{"id":"https://openalex.org/W4392445541","doi":"https://doi.org/10.1145/3616901.3616936","title":"A New Cardinality Estimation Method Based on Graph Neural Networks","display_name":"A New Cardinality Estimation Method Based on Graph Neural Networks","publication_year":2023,"publication_date":"2023-04-14","ids":{"openalex":"https://openalex.org/W4392445541","doi":"https://doi.org/10.1145/3616901.3616936"},"language":"en","primary_location":{"id":"doi:10.1145/3616901.3616936","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3616901.3616936","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 International Conference on Frontiers of Artificial Intelligence and Machine Learning","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/A5044710460","display_name":"Y. SONG","orcid":"https://orcid.org/0009-0004-0459-1677"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Feng Song","raw_affiliation_strings":["Information Center, University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0009-0004-0459-1677","affiliations":[{"raw_affiliation_string":"Information Center, University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113575711","display_name":"Xiao Dong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Dong Li","raw_affiliation_strings":["Information Center, University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0009-0008-1423-5077","affiliations":[{"raw_affiliation_string":"Information Center, University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080589294","display_name":"Dan Ni Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Ni Zhang","raw_affiliation_strings":["Informatization&Network Management Office, Southwest Jiaotong University, China"],"raw_orcid":"https://orcid.org/0009-0005-9562-459X","affiliations":[{"raw_affiliation_string":"Informatization&Network Management Office, Southwest Jiaotong University, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112117246","display_name":"Shu Huan Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Huan Fan","raw_affiliation_strings":["Information Center, University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0009-0003-9191-1968","affiliations":[{"raw_affiliation_string":"Information Center, University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030060251","display_name":"Dongsheng He","orcid":"https://orcid.org/0009-0009-4729-3078"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Sheng He","raw_affiliation_strings":["School of CSE University of Electronic Science and Technology of China, China"],"raw_orcid":"https://orcid.org/0009-0009-4729-3078","affiliations":[{"raw_affiliation_string":"School of CSE University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5044710460"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22001859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"153","last_page":"159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9959999918937683,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9959999918937683,"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"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9825000166893005,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9704999923706055,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7082405090332031},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.6148331165313721},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5568230152130127},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.463419109582901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3737030625343323},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.372386634349823},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.196914404630661}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7082405090332031},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.6148331165313721},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5568230152130127},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.463419109582901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3737030625343323},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.372386634349823},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.196914404630661}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3616901.3616936","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3616901.3616936","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 International Conference on Frontiers of Artificial Intelligence and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1822348499","https://openalex.org/W1947403449","https://openalex.org/W1968829657","https://openalex.org/W2021850646","https://openalex.org/W2053075747","https://openalex.org/W2081728040","https://openalex.org/W2100773341","https://openalex.org/W2109907545","https://openalex.org/W2153329411","https://openalex.org/W2158141386","https://openalex.org/W2766026698","https://openalex.org/W2795239330","https://openalex.org/W2890276152","https://openalex.org/W2911464154","https://openalex.org/W2911540814","https://openalex.org/W2924111053","https://openalex.org/W2950833175","https://openalex.org/W2971253019","https://openalex.org/W3105457604","https://openalex.org/W4246006899","https://openalex.org/W4255202827","https://openalex.org/W4300417575"],"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/W2124475651","https://openalex.org/W2585354854","https://openalex.org/W2064478620","https://openalex.org/W4308671316"],"abstract_inverted_index":{"Improving":[0],"the":[1,5,15,25,30,64,68,80,88,92,105,115,123,133,138],"query":[2,36,69,116],"performance":[3],"of":[4,33,67,83,91,98],"database":[6,16,26],"has":[7,20],"always":[8],"been":[9],"an":[10],"important":[11],"research":[12],"direction":[13],"in":[14,24,35,126,142],"field..":[17],"Deep":[18],"learning":[19],"shown":[21],"promising":[22],"applications":[23],"query.":[27],"To":[28],"utilise":[29],"distribution":[31],"features":[32,66],"data":[34,85,100],"optimization,":[37],"a":[38,57,95,128],"cardinality":[39,139],"estimation":[40,140],"method":[41,103,125],"GCE":[42,124],"(GNN":[43],"based":[44,47],"Cardinality":[45],"Estimation)":[46],"on":[48],"graph":[49,59,75],"neural":[50,60],"networks":[51,77],"is":[52],"proposed,":[53],"which":[54,73],"uses":[55,74],"Tree-LSTM,":[56],"tree":[58],"network,":[61],"to":[62,78,113],"extract":[63,79],"structural":[65],"plan":[70,108,112],"tree,":[71],"and":[72,87,109],"convolutional":[76],"association":[81],"relationship":[82,90],"each":[84],"column":[86],"topological":[89],"connection":[93],"through":[94],"high":[96],"level":[97],"historical":[99],"learning.":[101],"The":[102,118],"optimizes":[104],"logical":[106],"execution":[107,111],"physical":[110],"improve":[114],"accuracy.":[117],"experimental":[119],"results":[120],"show":[121],"that":[122],"TiDB,":[127],"distributed":[129],"relational":[130],"database,":[131],"improves":[132],"accuracy":[134],"twelvefold":[135],"compared":[136],"with":[137],"algorithm":[141],"TiDB.":[143]},"counts_by_year":[],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}