{"id":"https://openalex.org/W2118722427","doi":"https://doi.org/10.1145/1102351.1102468","title":"Hierarchical Dirichlet model for document classification","display_name":"Hierarchical Dirichlet model for document classification","publication_year":2005,"publication_date":"2005-01-01","ids":{"openalex":"https://openalex.org/W2118722427","doi":"https://doi.org/10.1145/1102351.1102468","mag":"2118722427"},"language":"en","primary_location":{"id":"doi:10.1145/1102351.1102468","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1102351.1102468","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd international conference on Machine learning  - ICML '05","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/A5024312309","display_name":"Sriharsha Veeramachaneni","orcid":null},"institutions":[{"id":"https://openalex.org/I4210097842","display_name":"Istituto Centrale per la Ricerca Scientifica e Tecnologica Applicata al Mare","ror":"https://ror.org/014cycx13","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210097842"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Sriharsha Veeramachaneni","raw_affiliation_strings":["SRA Division, Istituto per la ricerca scientifica e tecnologica (ITC-IRST), Trento, Italy"],"affiliations":[{"raw_affiliation_string":"SRA Division, Istituto per la ricerca scientifica e tecnologica (ITC-IRST), Trento, Italy","institution_ids":["https://openalex.org/I4210097842"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012525858","display_name":"Diego Sona","orcid":"https://orcid.org/0000-0003-2883-5336"},"institutions":[{"id":"https://openalex.org/I4210097842","display_name":"Istituto Centrale per la Ricerca Scientifica e Tecnologica Applicata al Mare","ror":"https://ror.org/014cycx13","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210097842"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Diego Sona","raw_affiliation_strings":["SRA Division, Istituto per la ricerca scientifica e tecnologica (ITC-IRST), Trento, Italy"],"affiliations":[{"raw_affiliation_string":"SRA Division, Istituto per la ricerca scientifica e tecnologica (ITC-IRST), Trento, Italy","institution_ids":["https://openalex.org/I4210097842"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060974774","display_name":"Paolo Avesani","orcid":"https://orcid.org/0000-0001-8943-8911"},"institutions":[{"id":"https://openalex.org/I4210097842","display_name":"Istituto Centrale per la Ricerca Scientifica e Tecnologica Applicata al Mare","ror":"https://ror.org/014cycx13","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210097842"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Avesani","raw_affiliation_strings":["SRA Division, Istituto per la ricerca scientifica e tecnologica (ITC-IRST), Trento, Italy"],"affiliations":[{"raw_affiliation_string":"SRA Division, Istituto per la ricerca scientifica e tecnologica (ITC-IRST), Trento, Italy","institution_ids":["https://openalex.org/I4210097842"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024312309"],"corresponding_institution_ids":["https://openalex.org/I4210097842"],"apc_list":null,"apc_paid":null,"fwci":4.1102,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.93981909,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"928","last_page":"935"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9966999888420105,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9966999888420105,"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/T10028","display_name":"Topic Modeling","score":0.9894999861717224,"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":0.9891999959945679,"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/computer-science","display_name":"Computer science","score":0.78326416015625},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.6359608173370361},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5828961730003357},{"id":"https://openalex.org/keywords/document-classification","display_name":"Document classification","score":0.5672828555107117},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5410467982292175},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.539114236831665},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5155367851257324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5104700326919556},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.44338011741638184},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.44007444381713867},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.434251606464386},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42025333642959595},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41923436522483826},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3942717909812927},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3916522264480591},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13403010368347168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.78326416015625},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.6359608173370361},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5828961730003357},{"id":"https://openalex.org/C2780479914","wikidata":"https://www.wikidata.org/wiki/Q302088","display_name":"Document classification","level":2,"score":0.5672828555107117},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5410467982292175},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.539114236831665},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5155367851257324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5104700326919556},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.44338011741638184},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.44007444381713867},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.434251606464386},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42025333642959595},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41923436522483826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3942717909812927},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3916522264480591},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13403010368347168},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1102351.1102468","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1102351.1102468","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd international conference on Machine learning  - ICML '05","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.80.8215","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.8215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://sra.itc.it/people/sona/PAPERS/veeramachaneni05hierarchical.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W140391703","https://openalex.org/W1518603657","https://openalex.org/W1523949738","https://openalex.org/W1525398599","https://openalex.org/W1602659231","https://openalex.org/W1621412722","https://openalex.org/W1660390307","https://openalex.org/W1751470192","https://openalex.org/W1800493452","https://openalex.org/W1880262756","https://openalex.org/W1991769471","https://openalex.org/W2063862666","https://openalex.org/W2070920590","https://openalex.org/W2094414211","https://openalex.org/W2117225622","https://openalex.org/W2118020653","https://openalex.org/W2144288153","https://openalex.org/W2161367368","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2529577912","https://openalex.org/W4313296694","https://openalex.org/W2001994797","https://openalex.org/W2952771778","https://openalex.org/W3103356223","https://openalex.org/W1520821320","https://openalex.org/W2084269532","https://openalex.org/W2782370056","https://openalex.org/W2130747910","https://openalex.org/W2102604346"],"abstract_inverted_index":{"The":[0,83],"proliferation":[1],"of":[2,21,36,69,76,99,110],"text":[3,24,59,77],"documents":[4,38,78],"on":[5,123],"the":[6,34,37,40,67,73,95,100,105,111],"web":[7,125],"as":[8,10],"well":[9],"within":[11],"institutions":[12],"necessitates":[13],"their":[14],"convenient":[15],"organization":[16],"to":[17,90,94],"enable":[18],"efficient":[19,64],"retrieval":[20],"information.":[22],"Although":[23],"corpora":[25,60],"are":[26,88],"frequently":[27],"organized":[28],"into":[29,39,79],"concept":[30],"hierarchies":[31],"or":[32,117],"taxonomies,":[33],"classification":[35,75,112],"hierarchy":[41],"is":[42],"expensive":[43],"in":[44,133],"terms":[45],"human":[46],"effort.":[47],"We":[48,102,119],"present":[49,120],"a":[50,80],"novel":[51],"and":[52,61,72],"simple":[53],"hierarchical":[54,96],"Dirichlet":[55],"generative":[56],"model":[57,70],"for":[58,66],"derive":[62],"an":[63],"algorithm":[65,106,129],"estimation":[68],"parameters":[71,113],"unsupervised":[74],"given":[81],"hierarchy.":[82],"class":[84],"conditional":[85],"feature":[86],"means":[87],"assumed":[89],"be":[91],"inter-related":[92],"due":[93],"Bayesian":[97],"structure":[98],"model.":[101],"show":[103],"that":[104,127],"provides":[107],"robust":[108],"estimates":[109],"by":[114],"performing":[115],"smoothing":[116],"regularization.":[118],"experimental":[121],"evidence":[122],"real":[124],"data":[126],"our":[128],"achieves":[130],"significant":[131],"gains":[132],"accuracy":[134],"over":[135],"simpler":[136],"models.":[137]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}