{"id":"https://openalex.org/W3210400704","doi":"https://doi.org/10.1145/3459637.3482060","title":"Attention Based Subgraph Classification for Link Prediction by Network Re-weighting","display_name":"Attention Based Subgraph Classification for Link Prediction by Network Re-weighting","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3210400704","doi":"https://doi.org/10.1145/3459637.3482060","mag":"3210400704"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482060","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","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/A5060590446","display_name":"Darong Lai","orcid":"https://orcid.org/0000-0002-8425-9954"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Darong Lai","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024691353","display_name":"Zheyi Liu","orcid":"https://orcid.org/0000-0003-0608-5482"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheyi Liu","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005731318","display_name":"Junyao Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyao Huang","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077748895","display_name":"Zhihong Chong","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Chong","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048871266","display_name":"Weiwei Wu","orcid":"https://orcid.org/0000-0001-9172-6955"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Wu","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081542076","display_name":"Christine Nardini","orcid":"https://orcid.org/0000-0001-7601-321X"},"institutions":[{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"funder","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Christine Nardini","raw_affiliation_strings":["National Research Council of Italy (CNR), Institute for Applied Mathematics(IAC)\"Mauro Picone\", Rome, Italy"],"affiliations":[{"raw_affiliation_string":"National Research Council of Italy (CNR), Institute for Applied Mathematics(IAC)\"Mauro Picone\", Rome, Italy","institution_ids":["https://openalex.org/I4210155236"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5060590446"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.3894,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60672054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3171","last_page":"3175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998000264167786,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.987500011920929,"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/weighting","display_name":"Weighting","score":0.7004609704017639},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.662416934967041},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.5251892805099487},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.5104023814201355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4667651355266571},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.45207077264785767},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4442337155342102},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3858640789985657},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.369629442691803},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35551899671554565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34621161222457886},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2879420220851898},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.08268359303474426}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7004609704017639},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.662416934967041},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.5251892805099487},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.5104023814201355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4667651355266571},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.45207077264785767},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4442337155342102},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3858640789985657},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.369629442691803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35551899671554565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34621161222457886},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2879420220851898},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.08268359303474426},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482060","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G5257540881","display_name":null,"funder_award_id":"2019YFB2102200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1994321911","https://openalex.org/W2003707464","https://openalex.org/W2054141820","https://openalex.org/W2095727900","https://openalex.org/W2338912252","https://openalex.org/W2742503211","https://openalex.org/W2788512147","https://openalex.org/W2962756421","https://openalex.org/W2962975498","https://openalex.org/W2999817249","https://openalex.org/W3015511536","https://openalex.org/W3094183418","https://openalex.org/W3159998597","https://openalex.org/W4238452917"],"related_works":["https://openalex.org/W2532922352","https://openalex.org/W2604893261","https://openalex.org/W2361654510","https://openalex.org/W1482551403","https://openalex.org/W2604114816","https://openalex.org/W2915540008","https://openalex.org/W2954463587","https://openalex.org/W2152074130","https://openalex.org/W2393701947","https://openalex.org/W2128390795"],"abstract_inverted_index":{"Supervised":[0],"link":[1,21,41,122,232],"prediction":[2,110,233],"aims":[3],"at":[4],"finding":[5],"missing":[6],"links":[7,139],"in":[8,80,87,133],"a":[9,34,94,115,131,147,154,175,225],"network":[10,127],"by":[11,126,182,214],"learning":[12,33],"directly":[13],"from":[14],"the":[15,54,57,68,118,134,141,151,161,165,170,179],"data":[16],"suitable":[17],"criteria":[18],"for":[19,108,157],"classifying":[20],"types":[22],"into":[23],"existent":[24],"or":[25,200],"non-existent.":[26],"Recently,":[27],"along":[28],"this":[29],"line,":[30],"subgraph-based":[31],"methods":[32],"function":[35,148],"that":[36,196],"maps":[37],"subgraph":[38,58,88,106,116,152,181],"patterns":[39],"to":[40,73,137,149,153,188,193,204],"existence":[42],"have":[43,51],"witnessed":[44],"great":[45],"successes.":[46],"However,":[47],"these":[48,92],"approaches":[49,72],"still":[50],"drawbacks.":[52],"First,":[53],"construction":[55],"of":[56,70,140,164,178,227],"relies":[59],"on":[60,224],"an":[61,84],"arbitrary":[62],"nodes":[63,76,81,120,185,189,206,211],"selection,":[64],"often":[65],"ineffective.":[66],"Second,":[67],"inability":[69],"such":[71],"evaluate":[74],"adaptively":[75,213],"importance":[77,212],"reduces":[78],"flexibility":[79],"features":[82,186],"aggregation,":[83],"important":[85],"step":[86],"classification.":[89],"To":[90],"address":[91],"issues,":[93],"novel":[95],"graph-classification":[96],"based":[97,105],"link-prediction":[98],"model":[99],"is":[100],"proposed:":[101],"Attention":[102],"and":[103,144],"Re-weighting":[104],"Classification":[107],"Link":[109],"(ARCLink).":[111],"ARCLink":[112,173,208,221],"first":[113],"extracts":[114],"around":[117],"two":[119],"whose":[121],"should":[123],"be":[124],"predicted,":[125],"reweighting,":[128],"i.e.":[129],"attributing":[130],"weight":[132],"range":[135],"0-1":[136],"all":[138],"original":[142],"network,":[143],"then":[145],"learns":[146,210],"map":[150],"continuous":[155],"vector":[156,176],"classification,":[158],"thus":[159],"revealing":[160],"nature":[162],"(non-existence/existence)":[163],"unknown":[166],"link.":[167],"For":[168],"leaning":[169],"mapping":[171],"function,":[172],"generates":[174],"representation":[177],"extracted":[180],"hierarchically":[183],"aggregating":[184],"according":[187],"importance.":[190],"In":[191],"contrast":[192],"previous":[194],"studies":[195],"either":[197],"fully":[198],"ignore":[199],"use":[201],"fixed":[202],"schemes":[203],"compute":[205],"importance,":[207],"instead":[209],"employing":[215],"attention":[216],"mechanism.":[217],"Through":[218],"extensive":[219],"experiments,":[220],"was":[222],"validated":[223],"series":[226],"real-world":[228],"networks":[229],"against":[230],"state-of-the-art":[231],"methods,":[234],"consistently":[235],"demonstrating":[236],"its":[237],"superior":[238],"performances":[239]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
