{"id":"https://openalex.org/W4210465888","doi":"https://doi.org/10.1109/taslp.2022.3145314","title":"HGEN: Learning Hierarchical Heterogeneous Graph Encoding for Math Word Problem Solving","display_name":"HGEN: Learning Hierarchical Heterogeneous Graph Encoding for Math Word Problem Solving","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4210465888","doi":"https://doi.org/10.1109/taslp.2022.3145314"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2022.3145314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2022.3145314","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-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/A5100388218","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-7731-0301"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007102035","display_name":"Guangyou Zhou","orcid":"https://orcid.org/0000-0002-7675-6619"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyou Zhou","raw_affiliation_strings":["School of Computer Science, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101705596","display_name":"Zhiwen Xie","orcid":"https://orcid.org/0000-0003-0837-3285"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Xie","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000409439","display_name":"Jimmy Xiangji Huang","orcid":"https://orcid.org/0000-0003-1292-1491"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jimmy Xiangji Huang","raw_affiliation_strings":["Information Retrieval and Knowledge Management Research Lab at the School of Information Technology, York University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Information Retrieval and Knowledge Management Research Lab at the School of Information Technology, York University, Toronto, Canada","institution_ids":["https://openalex.org/I192455969"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100388218"],"corresponding_institution_ids":["https://openalex.org/I40963666"],"apc_list":null,"apc_paid":null,"fwci":3.4485,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.93236531,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"30","issue":null,"first_page":"816","last_page":"828"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9955000281333923,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.972100019454956,"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/theoretical-computer-science","display_name":"Theoretical computer science","score":0.6466765999794006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6355045437812805},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.6209058165550232},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6176252365112305},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5917566418647766},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.5065990686416626},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.49327200651168823},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.47499337792396545},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4742159843444824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28731611371040344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2856770157814026}],"concepts":[{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.6466765999794006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6355045437812805},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.6209058165550232},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6176252365112305},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5917566418647766},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.5065990686416626},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.49327200651168823},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.47499337792396545},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4742159843444824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28731611371040344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2856770157814026},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2022.3145314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2022.3145314","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8500000238418579,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G8358453724","display_name":null,"funder_award_id":"61972173","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W167237087","https://openalex.org/W1506904803","https://openalex.org/W1539746312","https://openalex.org/W2003505241","https://openalex.org/W2013938288","https://openalex.org/W2072950331","https://openalex.org/W2105717194","https://openalex.org/W2152909313","https://openalex.org/W2157331557","https://openalex.org/W2250769864","https://openalex.org/W2251349042","https://openalex.org/W2251935656","https://openalex.org/W2252202991","https://openalex.org/W2276364082","https://openalex.org/W2329664754","https://openalex.org/W2399564521","https://openalex.org/W2475046758","https://openalex.org/W2510828927","https://openalex.org/W2513499049","https://openalex.org/W2561975193","https://openalex.org/W2757276219","https://openalex.org/W2758343314","https://openalex.org/W2905122540","https://openalex.org/W2911286998","https://openalex.org/W2951105272","https://openalex.org/W2951107864","https://openalex.org/W2962800603","https://openalex.org/W2962927633","https://openalex.org/W2963510263","https://openalex.org/W2963705839","https://openalex.org/W2963779892","https://openalex.org/W2964710271","https://openalex.org/W2965857891","https://openalex.org/W2970308008","https://openalex.org/W2971094176","https://openalex.org/W3034865274","https://openalex.org/W3035147733","https://openalex.org/W3035498813","https://openalex.org/W3101786725","https://openalex.org/W3102315106","https://openalex.org/W3106124812","https://openalex.org/W3108496296","https://openalex.org/W3115977017","https://openalex.org/W3161690523","https://openalex.org/W3173285067","https://openalex.org/W3174105824","https://openalex.org/W3174583470","https://openalex.org/W3174781928","https://openalex.org/W3175239873","https://openalex.org/W3176186248","https://openalex.org/W3192421672","https://openalex.org/W6630235389","https://openalex.org/W6630327132","https://openalex.org/W6631190155","https://openalex.org/W6636768068","https://openalex.org/W6714228854","https://openalex.org/W6726873649","https://openalex.org/W6745537798","https://openalex.org/W6747729229","https://openalex.org/W6752924033","https://openalex.org/W6755609140","https://openalex.org/W6760001035","https://openalex.org/W6767176353","https://openalex.org/W6769386472","https://openalex.org/W6779961489"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W1927327903","https://openalex.org/W1544665982","https://openalex.org/W4390516098","https://openalex.org/W2022479666","https://openalex.org/W2037549926","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2129146436","https://openalex.org/W2032507829"],"abstract_inverted_index":{"Designing":[0],"algorithms":[1],"to":[2,43,103],"solve":[3],"math":[4,28,32,54],"word":[5],"problems":[6],"(MWPs)":[7],"is":[8],"an":[9],"important":[10],"research":[11],"topic":[12],"in":[13,52,121,146],"natural":[14],"language":[15],"processing":[16],"and":[17,63,98],"smart":[18],"education":[19],"domains.":[20],"The":[21],"task":[22],"of":[23,67,93],"solving":[24],"MWPs":[25],"involves":[26],"transforming":[27],"problem":[29],"texts":[30],"into":[31],"equations.":[33],"Although":[34],"recent":[35],"Graph2Tree-based":[36,144],"models,":[37],"which":[38],"adopt":[39],"homogeneous":[40],"graph":[41,79,91],"encoders":[42],"learn":[44,104],"quantity":[45],"representations,":[46],"have":[47],"obtained":[48],"very":[49],"promising":[50],"results":[51,136],"generating":[53],"equations,":[55],"they":[56],"do":[57],"not":[58],"consider":[59],"the":[60,64,105,112,118,142,147],"heterogeneous":[61,68,78,90,106],"issue":[62],"long-distance":[65,113],"dependencies":[66],"nodes.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73],"propose":[74],"a":[75,89,94,99,122],"novel":[76],"hierarchical":[77,123],"encoding":[80],"called":[81],"HGEN":[82,86,109,139],"for":[83],"MWPs.":[84],"Specifically,":[85],"first":[87],"introduces":[88],"consisting":[92],"node-level":[95],"attention":[96,101],"layer":[97,102],"type-aware":[100],"node":[107],"embedding.":[108],"then":[110],"captures":[111],"dependent":[114],"information":[115],"by":[116],"propagating":[117],"multi-hop":[119],"nodes":[120],"manner.":[124],"We":[125],"conduct":[126],"extensive":[127],"experiments":[128],"on":[129],"two":[130],"popular":[131],"MWP":[132],"datasets.":[133],"Our":[134],"empirical":[135],"show":[137],"that":[138],"significantly":[140],"outperforms":[141],"state-of-the-art":[143],"models":[145],"literature.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-03T08:47:05.690250","created_date":"2025-10-10T00:00:00"}
