{"id":"https://openalex.org/W2092961325","doi":"https://doi.org/10.1145/2783258.2783264","title":"Diversifying Restricted Boltzmann Machine for Document Modeling","display_name":"Diversifying Restricted Boltzmann Machine for Document Modeling","publication_year":2015,"publication_date":"2015-08-07","ids":{"openalex":"https://openalex.org/W2092961325","doi":"https://doi.org/10.1145/2783258.2783264","mag":"2092961325"},"language":"en","primary_location":{"id":"doi:10.1145/2783258.2783264","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2783258.2783264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","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/A5083884675","display_name":"Pengtao Xie","orcid":"https://orcid.org/0000-0003-0521-174X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pengtao Xie","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088888805","display_name":"Yuntian Deng","orcid":"https://orcid.org/0000-0002-1257-1797"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuntian Deng","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009547049","display_name":"Eric P. Xing","orcid":"https://orcid.org/0009-0005-9158-4201"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric Xing","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083884675"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":6.7385,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.97844254,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1315","last_page":"1324"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9922999739646912,"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":0.745771050453186},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.668319821357727},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6519079804420471},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6483924388885498},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5654093623161316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5389699339866638},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.5212186574935913},{"id":"https://openalex.org/keywords/diversification","display_name":"Diversification (marketing strategy)","score":0.45554864406585693},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.43648552894592285},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39929890632629395},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3764267861843109},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.30529510974884033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.745771050453186},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.668319821357727},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6519079804420471},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6483924388885498},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5654093623161316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5389699339866638},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.5212186574935913},{"id":"https://openalex.org/C180916674","wikidata":"https://www.wikidata.org/wiki/Q3711935","display_name":"Diversification (marketing strategy)","level":2,"score":0.45554864406585693},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.43648552894592285},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39929890632629395},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3764267861843109},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30529510974884033},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2783258.2783264","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2783258.2783264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.721.5227","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.721.5227","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/%7Epengtaox/papers/kdd15_drbm.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G8266173613","display_name":null,"funder_award_id":"IIS1111142","funder_id":"https://openalex.org/F4320309090","funder_display_name":"Center for Hierarchical Manufacturing, National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320309090","display_name":"Center for Hierarchical Manufacturing, National Science Foundation","ror":"https://ror.org/043trmd87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W60843161","https://openalex.org/W100623710","https://openalex.org/W1423339008","https://openalex.org/W1546359014","https://openalex.org/W1612003148","https://openalex.org/W1813659000","https://openalex.org/W1853745982","https://openalex.org/W1880262756","https://openalex.org/W1995238279","https://openalex.org/W1995866178","https://openalex.org/W2009134948","https://openalex.org/W2024329736","https://openalex.org/W2024668293","https://openalex.org/W2087309226","https://openalex.org/W2100002341","https://openalex.org/W2110951295","https://openalex.org/W2116064496","https://openalex.org/W2136635436","https://openalex.org/W2138779671","https://openalex.org/W2153412625","https://openalex.org/W2157006255","https://openalex.org/W2163021329","https://openalex.org/W2169658215","https://openalex.org/W2197590357","https://openalex.org/W2525579820","https://openalex.org/W2559997609","https://openalex.org/W2597289420","https://openalex.org/W2604272474","https://openalex.org/W2754351509","https://openalex.org/W2949547296","https://openalex.org/W2950133940","https://openalex.org/W3103014337","https://openalex.org/W4205158545"],"related_works":["https://openalex.org/W2119341610","https://openalex.org/W4283272532","https://openalex.org/W2916681395","https://openalex.org/W2952018105","https://openalex.org/W2556473569","https://openalex.org/W4302433642","https://openalex.org/W1575733688","https://openalex.org/W2529583158","https://openalex.org/W2108438604","https://openalex.org/W2193475944"],"abstract_inverted_index":{"Restricted":[0],"Boltzmann":[1],"Machine":[2],"(RBM)":[3],"has":[4],"shown":[5],"great":[6],"effectiveness":[7],"in":[8,42,88,128],"document":[9,31,184,193],"modeling.":[10],"It":[11],"utilizes":[12],"hidden":[13,78,114,146],"units":[14,79,147],"to":[15,69,74,80,97,116,143,148,157],"discover":[16],"the":[17,62,89,94,113,122,129,145,152,170,192],"latent":[18],"topics":[19,41,54,60,84],"and":[20,34,85,100,137,166,186],"can":[21,177,198],"learn":[22,75],"compact":[23],"semantic":[24],"representations":[25,96],"for":[26],"documents":[27],"which":[28,92,111],"greatly":[29,200],"facilitate":[30],"retrieval,":[32],"clustering":[33,187],"classification.":[35],"The":[36],"popularity":[37],"(or":[38],"frequency)":[39],"of":[40,196],"text":[43],"corpora":[44],"usually":[45],"follow":[46],"a":[47,51,134,141],"power-law":[48],"distribution":[49],"where":[50],"few":[52],"dominant":[53,83,123],"occur":[55],"very":[56],"frequently":[57],"while":[58],"most":[59],"(in":[61],"long-tail":[63,90,130],"region)":[64],"have":[65],"low":[66],"probabilities.":[67],"Due":[68],"this":[70,104,179],"imbalance,":[71],"RBM":[72,109],"tends":[73],"multiple":[76],"redundant":[77,99],"best":[81],"represent":[82],"ignore":[86],"those":[87,127],"region,":[91],"renders":[93],"learned":[95],"be":[98,149,199],"non-informative.":[101],"To":[102],"solve":[103],"problem,":[105],"we":[106,160],"propose":[107],"Diversified":[108],"(DRBM)":[110],"diversifies":[112],"units,":[115],"make":[117],"them":[118],"cover":[119],"not":[120],"only":[121],"topics,":[124],"but":[125],"also":[126],"region.":[131],"We":[132],"define":[133],"diversity":[135,153,180],"metric":[136,154],"use":[138],"it":[139],"as":[140],"regularizer":[142],"encourage":[144],"diverse.":[150],"Since":[151],"is":[155],"hard":[156],"optimize":[158,162],"directly,":[159],"instead":[161],"its":[163],"lower":[164,171],"bound":[165,172],"prove":[167],"that":[168,189],"maximizing":[169],"with":[173,190],"projected":[174],"gradient":[175],"ascent":[176],"increase":[178],"metric.":[181],"Experiments":[182],"on":[183],"retrieval":[185],"demonstrate":[188],"diversification,":[191],"modeling":[194],"power":[195],"DRBM":[197],"improved.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":21},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}