{"id":"https://openalex.org/W4214704543","doi":"https://doi.org/10.1109/imcom53663.2022.9721720","title":"Improving a Graph-to-Tree Model for Solving Math Word Problems","display_name":"Improving a Graph-to-Tree Model for Solving Math Word Problems","publication_year":2022,"publication_date":"2022-01-03","ids":{"openalex":"https://openalex.org/W4214704543","doi":"https://doi.org/10.1109/imcom53663.2022.9721720"},"language":"en","primary_location":{"id":"doi:10.1109/imcom53663.2022.9721720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/imcom53663.2022.9721720","pdf_url":null,"source":{"id":"https://openalex.org/S4363608555","display_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","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/A5101796572","display_name":"Hyun-Ju Kim","orcid":"https://orcid.org/0000-0002-8093-3366"},"institutions":[{"id":"https://openalex.org/I4210135449","display_name":"NCSOFT (South Korea)","ror":"https://ror.org/03q4mza74","country_code":"KR","type":"company","lineage":["https://openalex.org/I4210135449"]},{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunju Kim","raw_affiliation_strings":["SungKyunKwan University (SKKU),Suwon,South Korea","SungKyunKwan University (SKKU), Suwon, South Korea","ESTsoft, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SungKyunKwan University (SKKU),Suwon,South Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"SungKyunKwan University (SKKU), Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"ESTsoft, Seoul, South Korea","institution_ids":["https://openalex.org/I4210135449"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015655159","display_name":"Junwon Hwang","orcid":null},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junwon Hwang","raw_affiliation_strings":["SungKyunKwan University (SKKU),Suwon,South Korea","SungKyunKwan University (SKKU), Suwon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SungKyunKwan University (SKKU),Suwon,South Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"SungKyunKwan University (SKKU), Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006638360","display_name":"Tae-Woo Yoo","orcid":null},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Taewoo Yoo","raw_affiliation_strings":["SungKyunKwan University (SKKU),Suwon,South Korea","SungKyunKwan University (SKKU), Suwon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SungKyunKwan University (SKKU),Suwon,South Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"SungKyunKwan University (SKKU), Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087179276","display_name":"Yun-Gyung Cheong","orcid":"https://orcid.org/0000-0001-6329-8439"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yun-Gyung Cheong","raw_affiliation_strings":["SungKyunKwan University (SKKU),Suwon,South Korea","SungKyunKwan University (SKKU), Suwon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SungKyunKwan University (SKKU),Suwon,South Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"SungKyunKwan University (SKKU), Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101796572"],"corresponding_institution_ids":["https://openalex.org/I4210135449","https://openalex.org/I848706"],"apc_list":null,"apc_paid":null,"fwci":0.5215,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61224165,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9994999766349792,"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/T10260","display_name":"Software Engineering Research","score":0.9902999997138977,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7766914367675781},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6002286076545715},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5830512642860413},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5822114944458008},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5449113845825195},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.5201581120491028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4599435031414032},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.4487053453922272},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4478422999382019},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4346761703491211},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.42710429430007935},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4199933707714081},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3511063754558563},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3461626172065735},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1463964283466339},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12262719869613647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7766914367675781},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6002286076545715},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5830512642860413},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5822114944458008},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5449113845825195},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.5201581120491028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4599435031414032},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.4487053453922272},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4478422999382019},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4346761703491211},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.42710429430007935},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4199933707714081},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3511063754558563},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3461626172065735},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1463964283466339},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12262719869613647},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/imcom53663.2022.9721720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/imcom53663.2022.9721720","pdf_url":null,"source":{"id":"https://openalex.org/S4363608555","display_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6200000047683716,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321378","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W25883864","https://openalex.org/W1505640990","https://openalex.org/W1539746312","https://openalex.org/W2003505241","https://openalex.org/W2092771413","https://openalex.org/W2105717194","https://openalex.org/W2250564385","https://openalex.org/W2250769864","https://openalex.org/W2251349042","https://openalex.org/W2251584889","https://openalex.org/W2251935656","https://openalex.org/W2252202991","https://openalex.org/W2276364082","https://openalex.org/W2475046758","https://openalex.org/W2513499049","https://openalex.org/W2757276219","https://openalex.org/W2786865417","https://openalex.org/W2788802500","https://openalex.org/W2796167946","https://openalex.org/W2798749466","https://openalex.org/W2890585661","https://openalex.org/W2898951026","https://openalex.org/W2950898568","https://openalex.org/W2951107864","https://openalex.org/W2954922414","https://openalex.org/W2963510263","https://openalex.org/W2963653811","https://openalex.org/W2963705839","https://openalex.org/W2963779892","https://openalex.org/W2964015378","https://openalex.org/W2964710271","https://openalex.org/W2971094176","https://openalex.org/W2998702685","https://openalex.org/W3034364750","https://openalex.org/W3034643750","https://openalex.org/W3035498813","https://openalex.org/W3106124812","https://openalex.org/W3127162741","https://openalex.org/W3170403598","https://openalex.org/W4288375838","https://openalex.org/W4294558607","https://openalex.org/W4297716178","https://openalex.org/W4297733535","https://openalex.org/W6630235389","https://openalex.org/W6690815549","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6748774801","https://openalex.org/W6749929118","https://openalex.org/W6752432587","https://openalex.org/W6755848887","https://openalex.org/W7002254874"],"related_works":["https://openalex.org/W2186864281","https://openalex.org/W4255427455","https://openalex.org/W4390516098","https://openalex.org/W1966025497","https://openalex.org/W68941528","https://openalex.org/W2181948922","https://openalex.org/W4206451355","https://openalex.org/W1553604823","https://openalex.org/W8322802","https://openalex.org/W2896411932"],"abstract_inverted_index":{"In":[0,92],"the":[1,37,61,104,111,117,128,145,155,163,176,196,199,208],"area":[2],"of":[3,23,63,100,106,116,198],"Math":[4],"Word":[5],"Problem":[6],"(MWP),":[7],"various":[8],"methods":[9,25,66,200,205],"based":[10,161],"on":[11,56,60,162,180],"deep":[12],"learning":[13],"technology":[14],"have":[15,206],"been":[16],"actively":[17],"researched.":[18],"Graph-to-Tree":[19],"(Graph2Tree)":[20],"is":[21,48],"one":[22],"those":[24],"which":[26,102],"uses":[27],"a":[28,32,43,140],"graph-based":[29,141],"encoder":[30,142],"and":[31,40,75,126,186,201],"tree-based":[33,156],"decoder":[34,157],"to":[35,41,50,80,109,132,143,158,171,193],"understand":[36,110],"word":[38,112],"problem":[39],"generate":[42,159],"valid":[44],"equation.":[45],"This":[46,138],"method":[47],"proven":[49],"be":[51],"well-performed":[52],"by":[53],"achieving":[54],"state-of-the-art":[55],"several":[57,83],"benchmarks.":[58],"However,":[59],"benchmark":[62],"SVAMP,":[64],"recent":[65],"including":[67],"Sequence-to-Sequence":[68],"(Seq2Seq),":[69],"Goal-driven":[70],"Tree-Structured":[71],"MWP":[72],"Solver":[73],"(GTS),":[74],"Graph2Tree":[76,101,119,178,210],"performs":[77],"poorly,":[78],"unable":[79],"cope":[81],"with":[82],"variation":[84],"types":[85],"that":[86,203],"requires":[87],"natural":[88,107],"language":[89,108],"comprehension":[90],"capability.":[91],"this":[93],"paper,":[94],"we":[95,121,150],"propose":[96],"an":[97],"improved":[98,207],"version":[99],"considers":[103],"characteristics":[105],"problems.":[113],"On":[114],"top":[115],"original":[118,177,209],"model,":[120],"additionally":[122],"build":[123],"Dependency":[124],"Graph":[125,131],"enhance":[127],"Quantity":[129,135],"Cell":[130,136],"Softly":[133],"Expanded":[134],"Graph.":[137],"helps":[139],"capture":[144],"relationship":[146],"among":[147],"words.":[148],"Also,":[149],"introduce":[151],"question":[152,164],"embedding":[153],"for":[154],"equation":[160],"given":[165],"as":[166],"input.":[167],"We":[168,188],"conduct":[169],"experiments":[170],"evaluate":[172],"our":[173,204],"model":[174,179],"against":[175],"three":[181],"available":[182],"datasets:":[183],"MAWPS,":[184],"ASDiv-A,":[185],"SVAMP.":[187],"also":[189],"present":[190],"case":[191],"studies":[192],"qualitatively":[194],"examine":[195],"effectiveness":[197],"showed":[202],"model.":[211]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}
