{"id":"https://openalex.org/W4385568381","doi":"https://doi.org/10.1145/3580305.3599339","title":"EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation","display_name":"EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568381","doi":"https://doi.org/10.1145/3580305.3599339"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599339","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5100673157","display_name":"Kuo Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kuo Yang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040516967","display_name":"Zhengyang Zhou","orcid":"https://orcid.org/0000-0003-4728-7347"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengyang Zhou","raw_affiliation_strings":["Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049128991","display_name":"Wei Sun","orcid":"https://orcid.org/0000-0002-5827-3787"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Sun","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103006792","display_name":"Pengkun Wang","orcid":"https://orcid.org/0000-0002-2680-4563"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengkun Wang","raw_affiliation_strings":["Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407848","display_name":"Xu Wang","orcid":"https://orcid.org/0000-0002-1492-3477"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101705851","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0002-6079-7053"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100673157"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":2.2305,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90242779,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2953","last_page":"2964"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9984999895095825,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.836106538772583},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.7760838270187378},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.583089292049408},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5545774102210999},{"id":"https://openalex.org/keywords/graph-factorization","display_name":"Graph factorization","score":0.4678077697753906},{"id":"https://openalex.org/keywords/distance-hereditary-graph","display_name":"Distance-hereditary graph","score":0.44838404655456543},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.38449883460998535},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37334197759628296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3558090031147003},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.16213321685791016}],"concepts":[{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.836106538772583},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.7760838270187378},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.583089292049408},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5545774102210999},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.4678077697753906},{"id":"https://openalex.org/C147792647","wikidata":"https://www.wikidata.org/wiki/Q5282847","display_name":"Distance-hereditary graph","level":5,"score":0.44838404655456543},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.38449883460998535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37334197759628296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3558090031147003},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.16213321685791016},{"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:10.1145/3580305.3599339","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1262889163","display_name":null,"funder_award_id":"62072427","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6058138561","display_name":null,"funder_award_id":", No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7584012289","display_name":null,"funder_award_id":"No.62072427, No.12227901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8298714682","display_name":null,"funder_award_id":"No.12227901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8646717170","display_name":null,"funder_award_id":"12227901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325599","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1993713305","https://openalex.org/W1994447879","https://openalex.org/W2008857988","https://openalex.org/W2056562706","https://openalex.org/W2099438806","https://openalex.org/W2133299088","https://openalex.org/W2154851992","https://openalex.org/W2558748708","https://openalex.org/W2898322439","https://openalex.org/W2997643818","https://openalex.org/W3016124664","https://openalex.org/W3033892090","https://openalex.org/W3036850272","https://openalex.org/W3090999459","https://openalex.org/W3094193403","https://openalex.org/W3100561866","https://openalex.org/W3104097132","https://openalex.org/W3105503635","https://openalex.org/W3153673236","https://openalex.org/W3169575312","https://openalex.org/W3171913066","https://openalex.org/W3205627238","https://openalex.org/W3210034512","https://openalex.org/W3215430231","https://openalex.org/W4224312868","https://openalex.org/W4224320982","https://openalex.org/W4283378708","https://openalex.org/W4287123803","https://openalex.org/W4290948450","https://openalex.org/W4312347724","https://openalex.org/W6733130978","https://openalex.org/W6775947557","https://openalex.org/W6779680381","https://openalex.org/W6784958482"],"related_works":["https://openalex.org/W2393701947","https://openalex.org/W2542507283","https://openalex.org/W167435155","https://openalex.org/W2886672068","https://openalex.org/W2953496651","https://openalex.org/W3208942821","https://openalex.org/W1512756268","https://openalex.org/W2604114816","https://openalex.org/W3151217588","https://openalex.org/W2397707437"],"abstract_inverted_index":{"Subgraph":[0],"learning":[1,18,61,113],"has":[2],"received":[3],"considerable":[4],"attention":[5],"in":[6,66,86,172],"its":[7],"capacity":[8],"of":[9,74,126,163,205,238],"interpreting":[10],"important":[11],"structural":[12],"information":[13,41,100,193],"for":[14,212],"predictions.":[15],"Existing":[16],"subgraph":[17,47,60,112,128,140,178],"usually":[19],"exploits":[20],"statistics":[21],"on":[22,55,59,217],"predefined":[23],"structures":[24],"e.g.,":[25],"node":[26,125],"degrees,":[27],"occurrence":[28],"frequency,":[29],"to":[30,102,176,189],"extract":[31,177],"subgraphs,":[32,199],"or":[33],"refine":[34],"the":[35,90,123,130,133,147,158,181,191,209,234],"contents":[36],"via":[37],"only":[38],"capturing":[39],"label-relevant":[40],"with":[42,52,165],"node-level":[43,84],"sampling.":[44],"Given":[45],"diverse":[46,218],"patterns,":[48],"and":[49,68,94,149,168,207,220,229,236],"mutual":[50,170,196],"independence":[51],"local":[53,92],"correlations":[54],"graphs,":[56],"current":[57],"solutions":[58],"still":[62,81],"have":[63],"two":[64],"limitations":[65],"extraction":[67,134,141],"refinement":[69,87,210],"stages.":[70],"1)":[71],"The":[72],"universality":[73,235],"extracting":[75],"substructure":[76],"patterns":[77],"across":[78,198],"domains":[79],"is":[80],"lacking,":[82],"2)":[83],"sampling":[85],"will":[88],"distort":[89],"original":[91],"topology":[93],"none":[95],"explicit":[96],"guidance":[97],"eliminating":[98],"redundant":[99],"contribute":[101],"inefficiency":[103],"issue.":[104],"In":[105,132,180],"this":[106,153],"paper,":[107],"we":[108,121,136,155,183],"propose":[109],"a":[110,138,185,202],"unified":[111],"scheme,":[114],"Poly-Pivot":[115],"Graph":[116],"Neural":[117],"Network":[118],"(P2GNN)":[119],"where":[120],"designate":[122],"centric":[124,148],"each":[127,161],"as":[129],"pivot.":[131],"stage,":[135],"present":[137],"general":[139],"principle,":[142],"i.e.,":[143],"Local;":[144],"Asymmetry":[145],"between":[146,160],"affiliated":[150],"nodes.":[151],"To":[152],"end,":[154],"asymmetrically":[156],"model":[157],"similarity":[159],"pair":[162],"nodes":[164],"random":[166],"walk":[167],"quantify":[169],"affiliations":[171],"Affinity":[173],"Propagation":[174],"architecture,":[175],"structures.":[179],"refinement,":[182],"devise":[184],"subgraph-level":[186],"exclusion":[187],"regularization":[188],"squash":[190],"target-independent":[192],"by":[194],"considering":[195],"relations":[197],"cooperatively":[200],"preserving":[201],"support":[203],"set":[204],"subgraphs":[206],"facilitating":[208],"process":[211],"graph":[213],"representation.":[214],"Empirical":[215],"experiments":[216],"web":[219],"biological":[221],"graphs":[222],"reveal":[223],"1.1%~7.3%":[224],"improvements":[225],"against":[226],"best":[227],"baselines,":[228],"visualized":[230],"case":[231],"studies":[232],"prove":[233],"interpretability":[237],"our":[239],"P2GNN.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
