{"id":"https://openalex.org/W3204133498","doi":"https://doi.org/10.1145/3459637.3482279","title":"Multi-Relational Graph based Heterogeneous Multi-Task Learning in Community Question Answering","display_name":"Multi-Relational Graph based Heterogeneous Multi-Task Learning in Community Question Answering","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3204133498","doi":"https://doi.org/10.1145/3459637.3482279","mag":"3204133498"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482279","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482279","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2110.02059","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zizheng Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Zizheng Lin","raw_affiliation_strings":["HKUST, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"HKUST, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haowen Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Haowen Ke","raw_affiliation_strings":["HKUST, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"HKUST, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ngo-Yin Wong","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ngo-Yin Wong","raw_affiliation_strings":["HKUST, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"HKUST, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiaxin Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jiaxin Bai","raw_affiliation_strings":["HKUST, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"HKUST, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yangqiu Song","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yangqiu Song","raw_affiliation_strings":["HKUST, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"HKUST, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Huan Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huan Zhao","raw_affiliation_strings":["4Paradigm Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"4Paradigm Inc., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Junpeng Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junpeng Ye","raw_affiliation_strings":["Tencent Technology (SZ) Co., Ltd., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent Technology (SZ) Co., Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I200769079"],"apc_list":null,"apc_paid":null,"fwci":0.6999,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76637731,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1038","last_page":"1047"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9973000288009644,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9968000054359436,"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/graph","display_name":"Graph","score":0.6193000078201294},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5931000113487244},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.44119998812675476},{"id":"https://openalex.org/keywords/graph-isomorphism","display_name":"Graph isomorphism","score":0.4343999922275543},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.365200012922287},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.35850000381469727},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.34630000591278076},{"id":"https://openalex.org/keywords/linked-data","display_name":"Linked data","score":0.3433000147342682},{"id":"https://openalex.org/keywords/graph-database","display_name":"Graph database","score":0.3312999904155731}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7383000254631042},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6193000078201294},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5931000113487244},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5184000134468079},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.44119998812675476},{"id":"https://openalex.org/C61665672","wikidata":"https://www.wikidata.org/wiki/Q303100","display_name":"Graph isomorphism","level":4,"score":0.4343999922275543},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42910000681877136},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.3433000147342682},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.3312999904155731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.3102000057697296},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2994000017642975},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2858999967575073},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C203436722","wikidata":"https://www.wikidata.org/wiki/Q902950","display_name":"Isomorphism (crystallography)","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.26080000400543213},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.25609999895095825}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3459637.3482279","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482279","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"},{"id":"pmh:oai:arXiv.org:2110.02059","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.02059","pdf_url":"https://arxiv.org/pdf/2110.02059","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-114830","is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2021&rft.spage=1038&rft.aulast=Lin&rft.aufirst=&rft.atitle=Multi-Relational+Graph+based+Heterogeneous+Multi-Task+Learning+in+Community+Question+Answering&rft.title=International+Conference+on+Information+and+Knowledge+Management%2C+Proceedings","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":"","raw_type":"Conference paper"},{"id":"pmh:oai:repository.ust.hk:1783.1-114830","is_oa":false,"landing_page_url":"http://repository.ust.hk/ir/Record/1783.1-114830","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":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2110.02059","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.02059","pdf_url":"https://arxiv.org/pdf/2110.02059","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1986945747","https://openalex.org/W1988115241","https://openalex.org/W1993535057","https://openalex.org/W2001831401","https://openalex.org/W2119295783","https://openalex.org/W2131774270","https://openalex.org/W2131876387","https://openalex.org/W2139956879","https://openalex.org/W2143331230","https://openalex.org/W2475334473","https://openalex.org/W2514077680","https://openalex.org/W2516255829","https://openalex.org/W2743159750","https://openalex.org/W2911286998","https://openalex.org/W2913340405","https://openalex.org/W2916264245","https://openalex.org/W2945266622","https://openalex.org/W2950692118","https://openalex.org/W2951105272","https://openalex.org/W3010865323","https://openalex.org/W3012871709","https://openalex.org/W3015135076","https://openalex.org/W3085258507"],"related_works":[],"abstract_inverted_index":{"Various":[0],"data":[1],"mining":[2],"tasks":[3,23,168],"have":[4,218],"been":[5],"proposed":[6,212],"to":[7,28,37,48,113,131,148,204],"study":[8],"Community":[9],"Question":[10],"Answering":[11],"(CQA)":[12],"platforms":[13],"like":[14],"Stack":[15,194],"Overflow.":[16,195],"The":[17,103,211],"relatedness":[18],"between":[19],"some":[20],"of":[21,41,96,155,165,172],"these":[22,42],"provides":[24],"useful":[25],"learning":[26],"signals":[27],"each":[29,82],"other":[30],"via":[31],"Multi-Task":[32,70],"Learning":[33],"(MTL).":[34],"However,":[35],"due":[36],"the":[38,88,123,133,137,139,153,160,170],"high":[39],"heterogeneity":[40],"tasks,":[43],"few":[44],"existing":[45],"works":[46],"manage":[47],"jointly":[49],"solve":[50],"them":[51],"in":[52],"a":[53,62,181],"unified":[54],"framework.":[55],"To":[56,152,175],"tackle":[57],"this":[58],"challenge,":[59],"we":[60,179],"develop":[61],"multi-relational":[63,173,184],"graph":[64,92,185],"based":[65,121],"MTL":[66,162,213],"model":[67,163],"called":[68],"Heterogeneous":[69],"Graph":[71,97],"Isomorphism":[72,98],"Network":[73,99],"(HMTGIN)":[74],"which":[75],"efficiently":[76],"solves":[77],"heterogeneous":[78],"CQA":[79,90,167,186],"tasks.":[80],"In":[81,136],"training":[83],"forward":[84],"pass,":[85],"HMTGIN":[86,158,201],"embeds":[87],"input":[89],"forum":[91],"by":[93],"an":[94],"extension":[95],"and":[100,215],"skip":[101],"connections.":[102],"embeddings":[104,140],"are":[105,129,141],"then":[106],"shared":[107,142],"across":[108],"all":[109,205],"task-specific":[110,145],"output":[111,146],"layers":[112,147],"compute":[114],"respective":[115],"losses.":[116],"Moreover,":[117],"two":[118,190],"cross-task":[119,216],"constraints":[120,217],"on":[122,207],"domain":[124],"knowledge":[125],"about":[126],"tasks'":[127],"relationships":[128],"used":[130],"regularize":[132],"joint":[134],"learning.":[135],"evaluation,":[138],"among":[143],"different":[144],"make":[149],"corresponding":[150],"predictions.":[151],"best":[154],"our":[156],"knowledge,":[157],"is":[159,202],"first":[161],"capable":[164],"tackling":[166],"from":[169,193],"aspect":[171],"graphs.":[174],"evaluate":[176],"HMTGIN's":[177],"effectiveness,":[178],"build":[180],"novel":[182],"large-scale":[183],"dataset":[187],"with":[188],"over":[189],"million":[191],"nodes":[192],"Extensive":[196],"experiments":[197],"show":[198],"that:":[199],"(1)":[200],"superior":[203],"baselines":[206],"five":[208],"tasks;":[209],"(2)":[210],"strategy":[214],"substantial":[219],"advantages.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-10-11T00:00:00"}
