{"id":"https://openalex.org/W3093551363","doi":"https://doi.org/10.1145/3340531.3411977","title":"Semi-Supervised Graph-to-Graph Translation","display_name":"Semi-Supervised Graph-to-Graph Translation","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3093551363","doi":"https://doi.org/10.1145/3340531.3411977","mag":"3093551363"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3411977","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411977","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 International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.08827","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tianxiang Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianxiang Zhao","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xianfeng Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xianfeng Tang","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":null,"display_name":"Suhang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhang Wang","raw_affiliation_strings":["Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":1.1499,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82650927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1863","last_page":"1872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9958000183105469,"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/T10028","display_name":"Topic Modeling","score":0.9919999837875366,"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/translation","display_name":"Translation (biology)","score":0.6047999858856201},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5393999814987183},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4578000009059906},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4131999909877777},{"id":"https://openalex.org/keywords/graph-rewriting","display_name":"Graph rewriting","score":0.39320001006126404},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.38580000400543213},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.36399999260902405},{"id":"https://openalex.org/keywords/directed-graph","display_name":"Directed graph","score":0.33799999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6610999703407288},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.6047999858856201},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5393999814987183},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5235999822616577},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4578000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4352000057697296},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4131999909877777},{"id":"https://openalex.org/C558772884","wikidata":"https://www.wikidata.org/wiki/Q1508564","display_name":"Graph rewriting","level":3,"score":0.39320001006126404},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.38580000400543213},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3781000077724457},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.36399999260902405},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C136979486","wikidata":"https://www.wikidata.org/wiki/Q773483","display_name":"Existential quantification","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2734000086784363},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2676999866962433},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3340531.3411977","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411977","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 International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2103.08827","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.08827","pdf_url":"https://arxiv.org/pdf/2103.08827","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.08827","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.08827","pdf_url":"https://arxiv.org/pdf/2103.08827","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1973705647","https://openalex.org/W2022322548","https://openalex.org/W2124187902","https://openalex.org/W2788134583","https://openalex.org/W2801116648","https://openalex.org/W2890007195","https://openalex.org/W2910453440","https://openalex.org/W2911752602","https://openalex.org/W2947249808","https://openalex.org/W2962790412","https://openalex.org/W2962801832","https://openalex.org/W4289436753"],"related_works":[],"abstract_inverted_index":{"Graph":[0,15],"translation":[1,27,48,101,113],"is":[2,16,51,57,86,109,128,151,185,203],"very":[3],"promising":[4],"research":[5],"direction":[6],"and":[7,23,25,76,124,137,198],"has":[8],"awide":[9],"range":[10],"of":[11,34,46,60,121,145,158,170,210],"potential":[12],"real-world":[13],"applications.":[14],"a":[17,82,99,164,179],"natural":[18],"structure":[19],"for":[20,167],"representing":[21,71,78],"relationship":[22],"interactions,":[24],"its":[26,41],"can":[28,67],"encode":[29],"the":[30,58,104,116,119,134,142,155,168,190,208,215],"intrinsic":[31],"semantic":[32,191],"changes":[33],"relation-ships":[35],"in":[36,103,118,147,218],"different":[37,220],"scenarios.":[38],"However,":[39],"despite":[40],"seemingly":[42],"wide":[43],"possibilities,":[44],"usage":[45],"graph":[47,100,112],"so":[49],"far":[50],"still":[52],"quite":[53],"limited.One":[54],"important":[55],"reason":[56],"lack":[59],"high-quality":[61],"paired":[62,84],"dataset.":[63],"For":[64],"example,":[65],"we":[66,95,175],"easily":[68],"build":[69],"graphs":[70],"peoples?":[72],"shared":[73],"music":[74],"tastes":[75],"those":[77],"co-purchase":[79],"behavior,":[80],"but":[81],"well":[83],"dataset":[85],"much":[87],"more":[88],"expensive":[89],"to":[90,97,130,133,141,153,177,188,206],"obtain.":[91],"Therefore,in":[92],"this":[93],"work,":[94],"seek":[96],"provide":[98],"model":[102,189],"semi-supervised":[105],"scenario.":[106],"This":[107],"task":[108],"non-trivial,":[110],"because":[111],"involves":[114],"changing":[115],"semantics":[117],"form":[120],"link":[122],"topology":[123],"node":[125],"attributes,":[126],"which":[127],"difficult":[129,152],"capture":[131],"due":[132,140],"combinatory":[135],"nature":[136],"inter-dependencies.":[138],"Furthermore,":[139],"high":[143],"order":[144],"freedom":[146],"graph's":[148],"composition,":[149],"it":[150],"assure":[154],"generalization":[156],"ability":[157],"trained":[159],"models.":[160],"These":[161],"difficulties":[162],"impose":[163],"tighter":[165],"requirement":[166],"exploitation":[169],"unpaired":[171],"samples.":[172],"Addressing":[173],"them,":[174],"propose":[176],"construct":[178],"dual":[180],"representation":[181],"space,":[182],"where":[183],"transformation":[184],"performed":[186],"explicitly":[187],"transitions.":[192],"Special":[193],"encoder/decoder":[194],"structures":[195],"are":[196],"designed,":[197],"auxiliary":[199],"mutual":[200],"information":[201],"loss":[202],"also":[204],"adopted":[205],"enforce":[207],"alignment":[209],"unpaired/paired":[211],"examples.":[212],"We":[213],"evaluate":[214],"proposed":[216],"method":[217],"three":[219],"datasets.":[221]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2020-10-29T00:00:00"}