{"id":"https://openalex.org/W4313491938","doi":"https://doi.org/10.1145/3570991.3571058","title":"Solving age-word problems using domain ontology and BERT","display_name":"Solving age-word problems using domain ontology and BERT","publication_year":2023,"publication_date":"2023-01-04","ids":{"openalex":"https://openalex.org/W4313491938","doi":"https://doi.org/10.1145/3570991.3571058"},"language":"en","primary_location":{"id":"doi:10.1145/3570991.3571058","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3570991.3571058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)","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/A5050867224","display_name":"Akshay Gupta","orcid":"https://orcid.org/0000-0002-3767-7408"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Akshay Gupta","raw_affiliation_strings":["Department of Computer Science & Engineering, IIT Madras, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, IIT Madras, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052991531","display_name":"Suresh Kumar","orcid":"https://orcid.org/0000-0003-4682-5721"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suresh Kumar","raw_affiliation_strings":["Department of Computer Science & Engineering, IIT Madras, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, IIT Madras, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059462350","display_name":"S P","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sreenivasa Kumar P","raw_affiliation_strings":["Department of Computer Science & Engineering, IIT Madras, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, IIT Madras, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050867224"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":0.3497,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61922527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"95","last_page":"103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9794999957084656,"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/T12031","display_name":"Speech and dialogue systems","score":0.9794999957084656,"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/T11977","display_name":"Technology Use by Older Adults","score":0.9606999754905701,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9581999778747559,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7759363651275635},{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.7410296201705933},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6388143301010132},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5868736505508423},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5370529890060425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4096538722515106},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1620720624923706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10708805918693542},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.08151674270629883},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.05208653211593628}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7759363651275635},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.7410296201705933},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6388143301010132},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5868736505508423},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5370529890060425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4096538722515106},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1620720624923706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10708805918693542},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.08151674270629883},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.05208653211593628},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3570991.3571058","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3570991.3571058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1577783107","https://openalex.org/W1847618513","https://openalex.org/W2041388851","https://openalex.org/W2072950331","https://openalex.org/W2105717194","https://openalex.org/W2250769864","https://openalex.org/W2251349042","https://openalex.org/W2251935656","https://openalex.org/W2276364082","https://openalex.org/W2510828927","https://openalex.org/W2757276219","https://openalex.org/W2905122540","https://openalex.org/W2951107864","https://openalex.org/W2962927633","https://openalex.org/W2963510263","https://openalex.org/W2963779892","https://openalex.org/W2964710271","https://openalex.org/W2971703667","https://openalex.org/W3173285067","https://openalex.org/W3192290435","https://openalex.org/W4239019441"],"related_works":["https://openalex.org/W2003333417","https://openalex.org/W2378862226","https://openalex.org/W118236634","https://openalex.org/W2355326633","https://openalex.org/W2804669904","https://openalex.org/W2149777447","https://openalex.org/W2347456287","https://openalex.org/W2121651557","https://openalex.org/W2782969047","https://openalex.org/W3204019825"],"abstract_inverted_index":{"An":[0,250],"age":[1,13,21,107],"word":[2,108],"problem":[3],"(ageWP)":[4],"typically":[5],"involves":[6],"sentences":[7,225],"that":[8,153,162,174,237,318],"express":[9],"relationships":[10,39],"between":[11,40],"the":[12,15,20,41,47,50,54,104,126,163,186,190,195,198,211,217,223,241,247,266,272,278,284,308],"of":[14,22,24,56,66,82,106,119,128,150,189,197,207,216,222,265,280,287,294],"agents":[16,129],"and":[17,45,110,160,230,258,298,311],"asks":[18],"for":[19,49,103,243,270,283],"one":[23,62],"them.":[25],"Automatically":[26],"solving":[27,141,286],"ageWPs":[28,83,124],"is":[29,72,253,274],"a":[30,77,98,116,131,155,204,232,261,288],"challenging":[31],"task":[32],"as":[33,260],"we":[34,96,138,172,193,202,291],"need":[35],"to":[36,75,113,168,180,185,239],"tackle":[37],"temporal":[38,86],"agent\u2019s":[42],"ages,":[43],"frame":[44],"solve":[46],"equations":[48],"required":[51],"unknowns.":[52],"To":[53,88],"best":[55],"our":[57,93,169],"knowledge,":[58],"there":[59],"exists":[60],"only":[61],"ageWP":[63,224],"dataset":[64,71,269],"consisting":[65,81],"just":[67],"124":[68],"examples.":[69],"The":[70,268,315],"too":[73],"small":[74],"employ":[76,299],"learning-based":[78,148],"solver,":[79],"mainly":[80],"with":[84,226,255,277,322],"simple":[85],"relationships.":[87],"address":[89],"this":[90,136,175],"issue,":[91],"in":[92,122,130,210,246],"earlier":[94],"work,":[95],"designed":[97],"description-logic":[99],"based":[100,213],"ontology":[101,196],"(ageWP-ont)":[102],"domain":[105,199],"problems":[109],"utilized":[111],"it":[112,209],"automatically":[114,275],"generate":[115],"large":[117],"number":[118],"ageWPs.":[120,191],"Sentences":[121],"these":[123,142,244,256],"relate":[125],"ages":[127],"temporally":[132],"complex":[133,187],"manner.":[134],"In":[135],"paper,":[137],"focus":[139],"on":[140,200],"problems.":[143],"We":[144,219,306],"analyzed":[145],"an":[146],"existing":[147],"solver":[149,164],"algebraic":[151],"word-problems":[152],"uses":[154],"traditional":[156],"machine":[157],"learning":[158,321],"approach":[159,176,206],"found":[161,173],"can":[165,324],"be":[166],"adapted":[167],"domain.":[170],"But":[171],"does":[177],"not":[178],"seem":[179],"perform":[181],"well,":[182],"perhaps":[183],"due":[184],"nature":[188],"As":[192],"have":[194],"hand,":[201],"propose":[203],"new":[205],"utilizing":[208],"deep-learning":[212],"NLU":[214],"component":[215],"solution.":[218],"annotate":[220],"parts":[221],"class-names":[227],"from":[228],"ageWP-ont":[229],"train":[231],"BERT-based":[233],"language":[234],"model":[235],"(LM)":[236],"learns":[238],"predict":[240],"instances":[242],"classes":[245],"given":[248,289],"sentences.":[249],"RDF":[251,296],"graph":[252,297],"populated":[254],"values":[257],"serves":[259],"concrete":[262],"problem-specific":[263],"instance":[264],"ontology.":[267],"training":[271],"LM":[273],"generated":[276],"help":[279],"ageWP-ont.":[281],"Finally,":[282],"actual":[285],"ageWP,":[290],"make":[292],"use":[293],"its":[295],"Semantic":[300],"Web":[301],"Rule":[302],"Language":[303],"(SWRL)":[304],"rules.":[305],"implemented":[307],"proposed":[309],"system":[310],"achieved":[312],"68.8%":[313],"accuracy.":[314],"work":[316],"demonstrates":[317],"combining":[319],"deep":[320],"ontologies":[323],"give":[325],"impressive":[326],"results.":[327]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}