{"id":"https://openalex.org/W2962833907","doi":"https://doi.org/10.1609/aaai.v33i01.3301265","title":"ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation","display_name":"ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2962833907","doi":"https://doi.org/10.1609/aaai.v33i01.3301265","mag":"2962833907"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.3301265","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.3301265","pdf_url":"https://aaai.org/ojs/index.php/AAAI/article/download/3794/3672","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://aaai.org/ojs/index.php/AAAI/article/download/3794/3672","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101424691","display_name":"Jiankai Sun","orcid":"https://orcid.org/0000-0002-7214-0665"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiankai Sun","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023057939","display_name":"Bortik Bandyopadhyay","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bortik Bandyopadhyay","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067348244","display_name":"Armin Bashizade","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Armin Bashizade","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072114538","display_name":"Jiongqian Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiongqian Liang","raw_affiliation_strings":["Ohio State University"],"affiliations":[{"raw_affiliation_string":"Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027517817","display_name":"P. Sadayappan","orcid":"https://orcid.org/0000-0002-4737-2034"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"P. Sadayappan","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100755351","display_name":"Srinivasan Parthasarathy","orcid":"https://orcid.org/0000-0002-6062-6449"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinivasan Parthasarathy","raw_affiliation_strings":["Ohio State University"],"affiliations":[{"raw_affiliation_string":"Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101424691"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":9.8176,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.98526214,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"33","issue":"01","first_page":"265","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.987500011920929,"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/embedding","display_name":"Embedding","score":0.6706743836402893},{"id":"https://openalex.org/keywords/reachability","display_name":"Reachability","score":0.668212890625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6553608179092407},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.593644917011261},{"id":"https://openalex.org/keywords/transitive-relation","display_name":"Transitive relation","score":0.580074667930603},{"id":"https://openalex.org/keywords/modular-decomposition","display_name":"Modular decomposition","score":0.5052435994148254},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.4536041021347046},{"id":"https://openalex.org/keywords/transitive-reduction","display_name":"Transitive reduction","score":0.45172399282455444},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4383181631565094},{"id":"https://openalex.org/keywords/directed-graph","display_name":"Directed graph","score":0.4319344460964203},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.42909151315689087},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42282670736312866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27585989236831665},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23710310459136963},{"id":"https://openalex.org/keywords/pathwidth","display_name":"Pathwidth","score":0.16202440857887268},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1323518455028534},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.10271579027175903},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09926232695579529},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.08529514074325562}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6706743836402893},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.668212890625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553608179092407},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.593644917011261},{"id":"https://openalex.org/C191399111","wikidata":"https://www.wikidata.org/wiki/Q64861","display_name":"Transitive relation","level":2,"score":0.580074667930603},{"id":"https://openalex.org/C187407849","wikidata":"https://www.wikidata.org/wiki/Q6889712","display_name":"Modular decomposition","level":5,"score":0.5052435994148254},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.4536041021347046},{"id":"https://openalex.org/C129691609","wikidata":"https://www.wikidata.org/wiki/Q3088151","display_name":"Transitive reduction","level":5,"score":0.45172399282455444},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4383181631565094},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.4319344460964203},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.42909151315689087},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42282670736312866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27585989236831665},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23710310459136963},{"id":"https://openalex.org/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.16202440857887268},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1323518455028534},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.10271579027175903},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09926232695579529},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.08529514074325562}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v33i01.3301265","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.3301265","pdf_url":"https://aaai.org/ojs/index.php/AAAI/article/download/3794/3672","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.3301265","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.3301265","pdf_url":"https://aaai.org/ojs/index.php/AAAI/article/download/3794/3672","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1154920154","display_name":null,"funder_award_id":"1513120","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1264843797","display_name":null,"funder_award_id":"IIS-1550302","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2739156970","display_name":"EAGER: Practical Graph Sparsification on GPUs","funder_award_id":"1550302","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3923288786","display_name":null,"funder_award_id":"CNS-1513120","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4318646374","display_name":"XPS: FULL: Collaborative Research: PARAGRAPH: Parallel, Scalable Graph Analytics","funder_award_id":"1629548","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4904952501","display_name":null,"funder_award_id":"CCF-1645599","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7873457385","display_name":"EAGER: Towards Automated Characterization of the Data-Movement Complexity of Large Scale Analytics Applications","funder_award_id":"1645599","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8585119406","display_name":null,"funder_award_id":"1520870","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962833907.pdf","grobid_xml":"https://content.openalex.org/works/W2962833907.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W43277809","https://openalex.org/W1888005072","https://openalex.org/W1941731038","https://openalex.org/W1994842363","https://openalex.org/W2017139167","https://openalex.org/W2115208659","https://openalex.org/W2122362506","https://openalex.org/W2126112131","https://openalex.org/W2149521292","https://openalex.org/W2153975459","https://openalex.org/W2154851992","https://openalex.org/W2240561375","https://openalex.org/W2242161203","https://openalex.org/W2294481449","https://openalex.org/W2294661159","https://openalex.org/W2387462954","https://openalex.org/W2561827022","https://openalex.org/W2574817444","https://openalex.org/W2578606145","https://openalex.org/W2588313843","https://openalex.org/W2604639157","https://openalex.org/W2604940557","https://openalex.org/W2605118682","https://openalex.org/W2605234117","https://openalex.org/W2612872092","https://openalex.org/W2739747431","https://openalex.org/W2761896323","https://openalex.org/W2770604839","https://openalex.org/W2787612455","https://openalex.org/W2796154789","https://openalex.org/W2949435814","https://openalex.org/W2963012037","https://openalex.org/W2963224980","https://openalex.org/W3103358463","https://openalex.org/W3103995645","https://openalex.org/W3105663903","https://openalex.org/W4297571622","https://openalex.org/W4300277754","https://openalex.org/W4307101379","https://openalex.org/W6690588655","https://openalex.org/W6707620307","https://openalex.org/W6731976766","https://openalex.org/W6733834428","https://openalex.org/W6736251384","https://openalex.org/W6736641260","https://openalex.org/W6936242187","https://openalex.org/W6948116018","https://openalex.org/W7055618970"],"related_works":["https://openalex.org/W2764268078","https://openalex.org/W2963892764","https://openalex.org/W2798731600","https://openalex.org/W3139713485","https://openalex.org/W2123134119","https://openalex.org/W2135565307","https://openalex.org/W4297795770","https://openalex.org/W1578808377","https://openalex.org/W2970143390","https://openalex.org/W3098656572"],"abstract_inverted_index":{"Directed":[0],"graphs":[1],"have":[2],"been":[3,76],"widely":[4],"used":[5],"in":[6,21,44,110,129,208,243],"Community":[7],"Question":[8,50],"Answering":[9],"services":[10],"(CQAs)":[11],"to":[12,68,105,113,121,165,176,241],"model":[13],"asymmetric":[14,59,95,179],"relationships":[15],"among":[16],"different":[17],"types":[18],"of":[19,34,58,79,90,239],"nodes":[20,227],"CQA":[22],"graphs,":[23,36],"e.g.,":[24],"question,":[25],"answer,":[26],"user.":[27],"Asymmetric":[28],"transitivity":[29,96],"is":[30],"an":[31,41],"essential":[32],"property":[33],"directed":[35,91],"since":[37],"it":[38],"can":[39,217,232],"play":[40],"important":[42],"role":[43],"downstream":[45],"graph":[46,67,92,134],"inference":[47],"and":[48,52,98,116,127,136,152,188,201,205,230,235],"analysis.":[49],"difficulty":[51,203],"user":[53],"expertise":[54,126],"follow":[55],"the":[56,66,77,88,101,124,149,159,174,178,191],"characteristic":[57],"transitivity.":[60,180],"Maintaining":[61],"such":[62,156],"properties,":[63],"while":[64],"reducing":[65],"a":[69,107,143,162],"lower":[70],"dimensional":[71],"vector":[72],"embedding":[73,93,103,168,220],"space,":[74],"has":[75],"focus":[78],"much":[80],"recent":[81],"research.":[82],"In":[83],"this":[84],"paper,":[85],"we":[86],"tackle":[87],"challenge":[89],"with":[94,123],"preservation":[97],"then":[99],"leverage":[100],"proposed":[102],"method":[104],"solve":[106],"fundamental":[108],"task":[109],"CQAs:":[111],"how":[112],"appropriately":[114],"route":[115,234],"assign":[117,236],"newly":[118,223],"posted":[119,224],"questions":[120,225,240],"users":[122],"suitable":[125],"interest":[128],"CQAs.":[130,244],"The":[131],"technique":[132],"incorporates":[133],"hierarchy":[135,154],"reachability":[137,151],"information":[138],"naturally":[139],"by":[140],"relying":[141],"on":[142,148,194],"nonlinear":[144],"transformation":[145],"that":[146,184],"operates":[147],"core":[150],"implicit":[153],"within":[155,173],"graphs.":[157],"Subsequently,":[158],"methodology":[160],"levers":[161],"factorization-based":[163],"approach":[164],"generate":[166],"two":[167],"vectors":[169],"for":[170,222],"each":[171],"node":[172],"graph,":[175],"capture":[177],"Extensive":[181],"experiments":[182],"show":[183],"our":[185,215],"framework":[186,216],"consistently":[187],"significantly":[189],"outperforms":[190],"state-of-the-art":[192],"baselines":[193],"three":[195],"diverse":[196],"realworld":[197],"tasks:":[198],"link":[199],"prediction,":[200],"question":[202],"estimation":[204],"expert":[206],"finding":[207],"online":[209],"forums":[210],"like":[211],"Stack":[212],"Exchange.":[213],"Particularly,":[214],"support":[218],"inductive":[219],"learning":[221],"(unseen":[226],"during":[228],"training),":[229],"therefore":[231],"properly":[233],"these":[237],"kinds":[238],"experts":[242]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
