{"id":"https://openalex.org/W2100132811","doi":"https://doi.org/10.3115/v1/p14-1098","title":"Structured Learning for Taxonomy Induction with Belief Propagation","display_name":"Structured Learning for Taxonomy Induction with Belief Propagation","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2100132811","doi":"https://doi.org/10.3115/v1/p14-1098","mag":"2100132811"},"language":"en","primary_location":{"id":"doi:10.3115/v1/p14-1098","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-1098","pdf_url":"https://aclanthology.org/P14-1098.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/P14-1098.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001987532","display_name":"Mohit Bansal","orcid":"https://orcid.org/0000-0001-5522-1351"},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohit Bansal","raw_affiliation_strings":["Toyota Technological Institute at Chicago, Chicago, United States"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute at Chicago, Chicago, United States","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003197445","display_name":"David Burkett","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Burkett","raw_affiliation_strings":["University of California, Berkeley, Berkeley, United States"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, United States","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085818578","display_name":"Gerard de Melo","orcid":"https://orcid.org/0000-0002-2930-2059"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gerard de Melo","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004921249","display_name":"Dan Klein","orcid":"https://orcid.org/0000-0002-8881-1902"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Klein","raw_affiliation_strings":["University of California, Berkeley, Berkeley, United States"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, United States","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001987532"],"corresponding_institution_ids":["https://openalex.org/I160992636"],"apc_list":null,"apc_paid":null,"fwci":7.1743,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":{"value":0.97053191,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1041","last_page":"1051"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994000196456909,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7356633543968201},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6702437400817871},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.6433951258659363},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.6290532350540161},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5912946462631226},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.5711154341697693},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5614702701568604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48302826285362244},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.47686395049095154},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4488697648048401},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43806013464927673},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.4138745665550232},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41142538189888},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.2646624445915222},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21275979280471802},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15229713916778564},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11814141273498535}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7356633543968201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6702437400817871},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.6433951258659363},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.6290532350540161},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5912946462631226},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.5711154341697693},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5614702701568604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48302826285362244},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.47686395049095154},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4488697648048401},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43806013464927673},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.4138745665550232},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41142538189888},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.2646624445915222},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21275979280471802},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15229713916778564},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11814141273498535},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"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":4,"locations":[{"id":"doi:10.3115/v1/p14-1098","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-1098","pdf_url":"https://aclanthology.org/P14-1098.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.470.42","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.470.42","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://nlp.cs.berkeley.edu/pubs/Bansal-etal_2014_Taxonomy_paper.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.648.2130","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.648.2130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ttic.uchicago.edu/~mbansal/papers/acl14_structuredTaxonomy.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.654.4239","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.654.4239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/P/P14/P14-1098.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/p14-1098","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-1098","pdf_url":"https://aclanthology.org/P14-1098.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G325743107","display_name":null,"funder_award_id":"61033001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4886626501","display_name":null,"funder_award_id":"2011CBA00301","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G680756813","display_name":null,"funder_award_id":"61033001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7219872841","display_name":null,"funder_award_id":"61361136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G741395852","display_name":null,"funder_award_id":"2011CBA00300, 2011CBA00301","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7798674883","display_name":null,"funder_award_id":"61033001, 61361136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G832729633","display_name":null,"funder_award_id":"61136003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8514270459","display_name":null,"funder_award_id":"61361136003","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8596328259","display_name":null,"funder_award_id":"6136113600","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8623030917","display_name":null,"funder_award_id":"2011CBA00300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2100132811.pdf","grobid_xml":"https://content.openalex.org/works/W2100132811.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W38703128","https://openalex.org/W1547207403","https://openalex.org/W1574662932","https://openalex.org/W1847921443","https://openalex.org/W1930023685","https://openalex.org/W1950142954","https://openalex.org/W1974383174","https://openalex.org/W1988615825","https://openalex.org/W1989115577","https://openalex.org/W1998325433","https://openalex.org/W2007756016","https://openalex.org/W2013109830","https://openalex.org/W2022166150","https://openalex.org/W2047032662","https://openalex.org/W2057052429","https://openalex.org/W2068737686","https://openalex.org/W2096956703","https://openalex.org/W2116671632","https://openalex.org/W2121855012","https://openalex.org/W2122922578","https://openalex.org/W2123982464","https://openalex.org/W2124206172","https://openalex.org/W2137023796","https://openalex.org/W2140259275","https://openalex.org/W2140480387","https://openalex.org/W2144108169","https://openalex.org/W2145328028","https://openalex.org/W2146502635","https://openalex.org/W2148540243","https://openalex.org/W2151386575","https://openalex.org/W2153653572","https://openalex.org/W2155734303","https://openalex.org/W2164370343","https://openalex.org/W2164732909","https://openalex.org/W2166776180","https://openalex.org/W2167061159","https://openalex.org/W2168432402","https://openalex.org/W2171278097","https://openalex.org/W2251021198","https://openalex.org/W2401961673","https://openalex.org/W2799004609","https://openalex.org/W2882319491","https://openalex.org/W2949620281","https://openalex.org/W2952509172","https://openalex.org/W2998508934","https://openalex.org/W4255198209"],"related_works":["https://openalex.org/W959529772","https://openalex.org/W4297812452","https://openalex.org/W2121846020","https://openalex.org/W1572864191","https://openalex.org/W4368755698","https://openalex.org/W4388627352","https://openalex.org/W2606077302","https://openalex.org/W2140575283","https://openalex.org/W3180766726","https://openalex.org/W2962950510"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,11,55,96,101,105,116],"structured":[3],"learning":[4],"approach":[5,94],"to":[6,77,110,122],"inducing":[7],"hypernym":[8],"taxonomies":[9],"using":[10,80],"probabilistic":[12],"graphical":[13],"model":[14,17],"formulation.":[15],"Our":[16],"incorporates":[18],"heterogeneous":[19],"relational":[20],"evidence":[21],"about":[22],"both":[23],"hypernymy":[24,63],"and":[25,34,39,74],"siblinghood,":[26],"captured":[27],"by":[28],"semantic":[29],"features":[30],"based":[31],"on":[32,130],"patterns":[33],"statistics":[35],"from":[36],"Web":[37],"n-grams":[38],"Wikipedia":[40],"abstracts.":[41],"For":[42],"efficient":[43],"inference":[44],"over":[45,100,127],"taxonomy":[46],"structures,":[47],"we":[48,69,119],"use":[49],"loopy":[50],"belief":[51],"propagation":[52],"along":[53],"with":[54],"directed":[56],"spanning":[57],"tree":[58],"algorithm":[59],"for":[60],"the":[61,67,86,111],"core":[62],"factor.":[64],"To":[65],"train":[66],"system,":[68],"extract":[70],"sub-structures":[71],"of":[72,88,91],"WordNet":[73],"discriminatively":[75],"learn":[76],"reproduce":[78],"them,":[79],"adaptive":[81],"subgradient":[82],"stochastic":[83],"optimization.":[84],"On":[85,115],"task":[87],"reproducing":[89],"sub-hierarchies":[90],"WordNet,":[92],"our":[93],"achieves":[95],"51%":[97],"error":[98,107,125],"reduction":[99,108,126],"chance":[102],"baseline,":[103],"including":[104],"15%":[106],"due":[109],"non-hypernym-factored":[112],"sibling":[113],"features.":[114],"comparison":[117],"setup,":[118],"find":[120],"up":[121],"29%":[123],"relative":[124],"previous":[128],"work":[129],"ancestor":[131],"F1.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":5},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
