{"id":"https://openalex.org/W2964003257","doi":"https://doi.org/10.1609/aaai.v33i01.33017394","title":"TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts","display_name":"TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2964003257","doi":"https://doi.org/10.1609/aaai.v33i01.33017394","mag":"2964003257"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33017394","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017394","pdf_url":null,"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":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v33i01.33017394","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005898634","display_name":"Michihiro Yasunaga","orcid":"https://orcid.org/0009-0003-3008-927X"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michihiro Yasunaga","raw_affiliation_strings":["Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060219657","display_name":"John Lafferty","orcid":"https://orcid.org/0000-0002-5929-220X"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John D. Lafferty","raw_affiliation_strings":["Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"01","first_page":"7394","last_page":"7401"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9510999917984009,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9253000020980835,"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/context","display_name":"Context (archaeology)","score":0.6906454563140869},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6705511808395386},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.6102087497711182},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5862781405448914},{"id":"https://openalex.org/keywords/structural-equation-modeling","display_name":"Structural equation modeling","score":0.5779069662094116},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5654899477958679},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5312775373458862},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.439385324716568},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.4346124529838562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38040128350257874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14086374640464783},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13462886214256287}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6906454563140869},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6705511808395386},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.6102087497711182},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5862781405448914},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.5779069662094116},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5654899477958679},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5312775373458862},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.439385324716568},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.4346124529838562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38040128350257874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14086374640464783},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13462886214256287},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33017394","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017394","pdf_url":null,"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"},{"id":"pmh:oai:ojs.aaai.org:article/4728","is_oa":true,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4728","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4728/4606","source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33017394","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017394","pdf_url":null,"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":[{"id":"https://metadata.un.org/sdg/4","score":0.8100000023841858,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W1522301498","https://openalex.org/W1815076433","https://openalex.org/W1959608418","https://openalex.org/W1999965501","https://openalex.org/W2092961325","https://openalex.org/W2095705004","https://openalex.org/W2100163972","https://openalex.org/W2108612889","https://openalex.org/W2130339025","https://openalex.org/W2140313579","https://openalex.org/W2147946282","https://openalex.org/W2157006255","https://openalex.org/W2159426623","https://openalex.org/W2160507407","https://openalex.org/W2166354010","https://openalex.org/W2173681125","https://openalex.org/W2197590357","https://openalex.org/W2250533720","https://openalex.org/W2259472270","https://openalex.org/W2337021505","https://openalex.org/W2396820472","https://openalex.org/W2402218232","https://openalex.org/W2476140796","https://openalex.org/W2524879642","https://openalex.org/W2549476280","https://openalex.org/W2594155836","https://openalex.org/W2621133045","https://openalex.org/W2626873800","https://openalex.org/W2778817245","https://openalex.org/W2804018630","https://openalex.org/W2952478253","https://openalex.org/W2962966012","https://openalex.org/W2963537774","https://openalex.org/W2964186239","https://openalex.org/W3099640513","https://openalex.org/W4231510805","https://openalex.org/W4237840503","https://openalex.org/W4248892431","https://openalex.org/W4394663071","https://openalex.org/W6607333740","https://openalex.org/W6631190155","https://openalex.org/W6639619044","https://openalex.org/W6640963894","https://openalex.org/W6655670753","https://openalex.org/W6666761814","https://openalex.org/W6668529637","https://openalex.org/W6671196654","https://openalex.org/W6679482899","https://openalex.org/W6682044806","https://openalex.org/W6683240801","https://openalex.org/W6684232553","https://openalex.org/W6685356407","https://openalex.org/W6712896552","https://openalex.org/W6736833339","https://openalex.org/W6740017710","https://openalex.org/W6747516836","https://openalex.org/W6785094883"],"related_works":["https://openalex.org/W3158636765","https://openalex.org/W4295177495","https://openalex.org/W4287636269","https://openalex.org/W2399306074","https://openalex.org/W2899106999","https://openalex.org/W2171278750","https://openalex.org/W4294377911","https://openalex.org/W4293581809","https://openalex.org/W2950770596","https://openalex.org/W2161353674"],"abstract_inverted_index":{"Scientific":[0],"documents":[1],"rely":[2],"on":[3,70],"both":[4],"mathematics":[5],"and":[6,19,37,60,97,118,137,150,156],"text":[7,40],"to":[8],"communicate":[9],"ideas.":[10],"Inspired":[11],"by":[12,65],"the":[13,46,50,61,71,99,129,133],"topical":[14],"correspondence":[15],"between":[16,135],"mathematical":[17,35,154],"equations":[18,36],"word":[20],"contexts":[21],"observed":[22],"in":[23],"scientific":[24,93,122],"texts,":[25],"we":[26,80,125],"propose":[27],"a":[28,55,82,90,102],"novel":[29,140],"topic":[30,48,73,116,148],"model":[31,100,112,130],"that":[32,68,109,128],"jointly":[33],"generates":[34],"their":[38],"surrounding":[39],"(TopicEq).":[41],"Using":[42],"an":[43,66],"extension":[44],"of":[45,57,84,92,153],"correlated":[47],"model,":[49,79],"context":[51],"is":[52,63],"generated":[53,64],"from":[54,89,95],"mixture":[56],"latent":[58,72],"topics,":[59],"equation":[62,119,145,147],"RNN":[67],"depends":[69],"activations.":[74],"To":[75],"experiment":[76],"with":[77],"this":[78,110],"create":[81],"corpus":[83],"400K":[85],"equation-context":[86],"pairs":[87],"extracted":[88],"range":[91],"articles":[94],"arXiv,":[96],"fit":[98],"using":[101],"variational":[103],"autoencoder":[104],"approach.":[105],"Experimental":[106],"results":[107],"show":[108,127],"joint":[111],"significantly":[113],"outperforms":[114],"existing":[115],"models":[117,120],"for":[121],"texts.":[123],"Moreover,":[124],"qualitatively":[126],"effectively":[131],"captures":[132],"relationship":[134],"topics":[136],"mathematics,":[138],"enabling":[139],"applications":[141],"such":[142],"as":[143],"topic-aware":[144,151],"generation,":[146],"inference,":[149],"alignment":[152],"symbols":[155],"words.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
