{"id":"https://openalex.org/W4367047402","doi":"https://doi.org/10.1145/3543507.3583401","title":"Knowledge Graph Completion with Counterfactual Augmentation","display_name":"Knowledge Graph Completion with Counterfactual Augmentation","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367047402","doi":"https://doi.org/10.1145/3543507.3583401"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583401","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","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/A5027050251","display_name":"Heng Chang","orcid":"https://orcid.org/0000-0002-4978-8041"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Heng Chang","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074199725","display_name":"Jie Cai","orcid":"https://orcid.org/0000-0003-2191-8585"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Cai","raw_affiliation_strings":["Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100405697","display_name":"Jia Li","orcid":"https://orcid.org/0000-0002-6362-4385"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia Li","raw_affiliation_strings":["Hong Kong University of Science and Technology (Guangzhou), China"],"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology (Guangzhou), China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027050251"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.5387,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.95728959,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2611","last_page":"2620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9868000149726868,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9800000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7228343486785889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6211545467376709},{"id":"https://openalex.org/keywords/completion","display_name":"Completion (oil and gas wells)","score":0.47726672887802124},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.47152671217918396},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44690555334091187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21315142512321472},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15771862864494324},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15177705883979797},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09399110078811646}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7228343486785889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6211545467376709},{"id":"https://openalex.org/C2779538338","wikidata":"https://www.wikidata.org/wiki/Q2990590","display_name":"Completion (oil and gas wells)","level":2,"score":0.47726672887802124},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.47152671217918396},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44690555334091187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21315142512321472},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15771862864494324},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15177705883979797},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09399110078811646},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3543507.3583401","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-157921","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-157921","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2107306718","https://openalex.org/W2151502664","https://openalex.org/W2250184916","https://openalex.org/W2250601658","https://openalex.org/W2728059831","https://openalex.org/W2885711033","https://openalex.org/W2912708407","https://openalex.org/W2914592219","https://openalex.org/W2950393809","https://openalex.org/W2952179887","https://openalex.org/W2962756421","https://openalex.org/W2970823335","https://openalex.org/W2997404190","https://openalex.org/W2997897037","https://openalex.org/W3003265726","https://openalex.org/W3005312434","https://openalex.org/W3011667710","https://openalex.org/W3016124664","https://openalex.org/W3085131702","https://openalex.org/W3095746859","https://openalex.org/W3103296573","https://openalex.org/W3154503084","https://openalex.org/W3160381762","https://openalex.org/W3195761992","https://openalex.org/W3201541168","https://openalex.org/W3208390110","https://openalex.org/W4221160815","https://openalex.org/W4224878657","https://openalex.org/W4236213345","https://openalex.org/W4281561077","https://openalex.org/W4282943426","https://openalex.org/W4283818721","https://openalex.org/W4288087297","https://openalex.org/W4290943920","https://openalex.org/W4311079930","https://openalex.org/W6775947557","https://openalex.org/W6782808188"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3201448254","https://openalex.org/W4286970243","https://openalex.org/W2066431708","https://openalex.org/W4384133558","https://openalex.org/W3025615835","https://openalex.org/W173210993","https://openalex.org/W2390660599"],"abstract_inverted_index":{"Graph":[0,10],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4,39],"demonstrated":[5],"great":[6],"success":[7],"in":[8,20],"Knowledge":[9],"Completion":[11],"(KGC)":[12],"by":[13,48,103],"modeling":[14],"how":[15],"entities":[16,54,76],"and":[17,121,155],"relations":[18,98,136],"interact":[19],"recent":[21],"years.":[22],"However,":[23],"most":[24],"of":[25,75,86,107,116,123,147,172,191,199],"them":[26],"are":[27],"designed":[28,84],"to":[29,38,99,143],"learn":[30],"from":[31,79,151],"the":[32,44,49,53,68,73,91,96,101,105,124,128,133,138,153,170,182,189,192,196],"observed":[33,154],"graph":[34],"structure,":[35],"which":[36],"appears":[37],"imbalanced":[40],"relation":[41,69,111],"distribution":[42],"during":[43],"training":[45],"stage.":[46],"Motivated":[47],"causal":[50,88],"relationship":[51],"among":[52],"on":[55,90,141,159,169],"a":[56,64,82,87],"knowledge":[57,92],"graph,":[58,93],"we":[59,94,131,179],"explore":[60],"this":[61],"defect":[62],"through":[63,195],"counterfactual":[65,97,135,156,184],"question:":[66],"\u201cwould":[67],"still":[70],"exist":[71],"if":[72],"neighborhood":[74,118],"became":[77],"different":[78],"observation?\u201d.":[80],"With":[81],"carefully":[83],"instantiation":[85],"model":[89],"generate":[95],"answer":[100],"question":[102],"regarding":[104],"representations":[106,150],"entity":[108,148],"pair":[109,149],"given":[110],"as":[112,119,127],"context,":[113],"structural":[114],"information":[115],"relation-aware":[117],"treatment,":[120],"validity":[122],"composed":[125],"triplet":[126],"outcome.":[129],"Furthermore,":[130],"incorporate":[132],"created":[134],"with":[137],"GNN-based":[139,193],"framework":[140,194],"KGs":[142],"augment":[144],"their":[145],"learning":[146],"both":[152],"relations.":[157],"Experiments":[158],"benchmarks":[160],"show":[161],"that":[162,181],"our":[163],"proposed":[164,183],"method":[165],"outperforms":[166],"existing":[167],"methods":[168],"task":[171],"KGC,":[173],"achieving":[174],"new":[175],"state-of-the-art":[176],"results.":[177],"Moreover,":[178],"demonstrate":[180],"relations-based":[185],"augmentation":[186],"also":[187],"enhances":[188],"interpretability":[190],"path":[197],"interpretations":[198],"predictions.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":4}],"updated_date":"2026-02-26T08:16:20.718346","created_date":"2025-10-10T00:00:00"}
