{"id":"https://openalex.org/W3201511955","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534093","title":"Automatic Topic Labeling model with Paired-Attention based on Pre-trained Deep Neural Network","display_name":"Automatic Topic Labeling model with Paired-Attention based on Pre-trained Deep Neural Network","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201511955","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534093","mag":"3201511955"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534093","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5071506058","display_name":"Dongbin He","orcid":"https://orcid.org/0000-0001-6197-5192"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongbin He","raw_affiliation_strings":["China Agricultural University,College of Information and Electrical Engineering,Beijing,China","College of Information and Electrical Engineering, China Agricultural University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Agricultural University,College of Information and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Information and Electrical Engineering, China Agricultural University, Beijing, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110692342","display_name":"Yanzhao Ren","orcid":"https://orcid.org/0000-0002-2148-6615"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanzhao Ren","raw_affiliation_strings":["China Agricultural University,College of Science,Beijing,China","College of Science, China Agricultural University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Agricultural University,College of Science,Beijing,China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Science, China Agricultural University, Beijing, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000178744","display_name":"Abdul Mateen Khattak","orcid":"https://orcid.org/0000-0003-4417-489X"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Abdul Mateen Khattak","raw_affiliation_strings":["China Agricultural University,College of Information and Electrical Engineering,Beijing,China","College of Information and Electrical Engineering, China Agricultural University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Agricultural University,College of Information and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Information and Electrical Engineering, China Agricultural University, Beijing, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100619255","display_name":"Xinliang Liu","orcid":"https://orcid.org/0000-0003-4397-1969"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinliang Liu","raw_affiliation_strings":["China Agricultural University,College of Information and Electrical Engineering,Beijing,China","College of Information and Electrical Engineering, China Agricultural University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Agricultural University,College of Information and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Information and Electrical Engineering, China Agricultural University, Beijing, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103063658","display_name":"Sha Tao","orcid":"https://orcid.org/0000-0002-8839-7705"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sha Tao","raw_affiliation_strings":["China Agricultural University,College of Information and Electrical Engineering,Beijing,China","College of Information and Electrical Engineering, China Agricultural University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Agricultural University,College of Information and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Information and Electrical Engineering, China Agricultural University, Beijing, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013019306","display_name":"Wanlin Gao","orcid":"https://orcid.org/0000-0002-4845-4541"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanlin Gao","raw_affiliation_strings":["China Agricultural University,College of Information and Electrical Engineering,Beijing,China","College of Information and Electrical Engineering, China Agricultural University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Agricultural University,College of Information and Electrical Engineering,Beijing,China","institution_ids":["https://openalex.org/I52158045"]},{"raw_affiliation_string":"College of Information and Electrical Engineering, China Agricultural University, Beijing, China","institution_ids":["https://openalex.org/I52158045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5071506058"],"corresponding_institution_ids":["https://openalex.org/I52158045"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63539676,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9998999834060669,"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":0.9998000264167786,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9958999752998352,"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":0.8577869534492493},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8197201490402222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6348763108253479},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5975574254989624},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5396274924278259},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.53883957862854},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5337373614311218},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5293750762939453},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5178499817848206},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4357983469963074},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4195864200592041},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4094652235507965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8577869534492493},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8197201490402222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6348763108253479},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5975574254989624},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5396274924278259},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.53883957862854},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5337373614311218},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5293750762939453},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5178499817848206},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4357983469963074},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4195864200592041},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4094652235507965},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534093","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5199999809265137,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G8685360593","display_name":null,"funder_award_id":"31801669","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W75235505","https://openalex.org/W1525595230","https://openalex.org/W1614298861","https://openalex.org/W1753361524","https://openalex.org/W1880262756","https://openalex.org/W1910962341","https://openalex.org/W2005952540","https://openalex.org/W2059834155","https://openalex.org/W2097807612","https://openalex.org/W2106224734","https://openalex.org/W2110693578","https://openalex.org/W2113499583","https://openalex.org/W2113855231","https://openalex.org/W2123495014","https://openalex.org/W2131744502","https://openalex.org/W2250355330","https://openalex.org/W2250448630","https://openalex.org/W2293301714","https://openalex.org/W2401143219","https://openalex.org/W2509005432","https://openalex.org/W2573170368","https://openalex.org/W2574535369","https://openalex.org/W2620851716","https://openalex.org/W2741018521","https://openalex.org/W2896457183","https://openalex.org/W2909544278","https://openalex.org/W2924690340","https://openalex.org/W2949807892","https://openalex.org/W2950577311","https://openalex.org/W2952138241","https://openalex.org/W2953300870","https://openalex.org/W2963006164","https://openalex.org/W2963185411","https://openalex.org/W2963311768","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2970419734","https://openalex.org/W2970785793","https://openalex.org/W2972849480","https://openalex.org/W2980340704","https://openalex.org/W2998939484","https://openalex.org/W3101913037","https://openalex.org/W4240337468","https://openalex.org/W4300427681","https://openalex.org/W4302990361","https://openalex.org/W4385245566","https://openalex.org/W6631501603","https://openalex.org/W6636510571","https://openalex.org/W6639619044","https://openalex.org/W6675841840","https://openalex.org/W6679775712","https://openalex.org/W6691222388","https://openalex.org/W6730858672","https://openalex.org/W6731888841","https://openalex.org/W6731948947","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6758015726","https://openalex.org/W6761268247","https://openalex.org/W6780226713","https://openalex.org/W6987714012"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W1517524280"],"abstract_inverted_index":{"The":[0,156],"automatic":[1],"topic":[2,13,50,73,114,169],"labeling":[3,51,170],"model":[4,47,62,94,162],"aims":[5],"at":[6],"generating":[7],"a":[8,72,83,136],"sound,":[9],"interpretable,":[10],"and":[11,79,102,167],"meaningful":[12],"label":[14,74],"that":[15,119,160],"is":[16],"used":[17],"to":[18,25,49,63,93,139],"interpret":[19],"an":[20],"LDA-style":[21],"discovered":[22,132],"topic,":[23,133],"intending":[24],"reduce":[26],"the":[27,36,44,55,59,65,91,95,98,111,141,146,153,165],"cognitive":[28],"load":[29],"of":[30,58,67],"end-users":[31],"while":[32],"browsing":[33],"or":[34],"investigating":[35],"topics.":[37],"In":[38],"this":[39],"study,":[40],"we":[41,81,117,134],"first":[42,101],"introduced":[43],"pre-trained":[45,60],"language":[46,61],"BERT":[48],"tasks.":[52],"It":[53],"exploits":[54,90],"contextual":[56],"embedding":[57],"improve":[64,125],"quality":[66],"encoding":[68,122],"sentences.":[69],"To":[70],"generate":[71],"with":[75],"higher":[76],"Relevance,":[77],"Coverage,":[78],"Discrimination,":[80],"propose":[82],"novel":[84],"summarization":[85,113],"neural":[86],"framework.":[87],"Specifically,":[88],"it":[89],"paired-attention":[92],"relationship":[96],"between":[97],"candidate":[99],"sentences":[100,106],"then":[103],"decides":[104],"which":[105],"should":[107],"be":[108],"included":[109],"in":[110],"final":[112],"label.":[115],"Moreover,":[116],"expected":[118],"high-quality":[120],"sentence":[121,147],"representation":[123],"could":[124],"our":[126,161],"model's":[127],"performance.":[128],"So,":[129],"for":[130],"each":[131],"trained":[135],"specific":[137],"layer":[138],"extract":[140],"important":[142],"topic-related":[143],"features":[144],"from":[145],"embeddings":[148],"as":[149,151],"well":[150],"filter":[152],"noise":[154],"information.":[155],"experimental":[157],"results":[158],"showed":[159],"significantly":[163],"outperforms":[164],"state-of-the-art":[166],"classic":[168],"models.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
