{"id":"https://openalex.org/W2802103240","doi":"https://doi.org/10.1109/icassp.2018.8461673","title":"Joint Verification-Identification in end-to-end Multi-Scale CNN Framework for Topic Identification","display_name":"Joint Verification-Identification in end-to-end Multi-Scale CNN Framework for Topic Identification","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2802103240","doi":"https://doi.org/10.1109/icassp.2018.8461673","mag":"2802103240"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8461673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5040448607","display_name":"Raghavendra Pappagari","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raghavendra Pappagari","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057010207","display_name":"Jes\u00fas Villalba","orcid":"https://orcid.org/0000-0001-9459-8426"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jesus Villalba","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050632169","display_name":"Najim Dehak","orcid":"https://orcid.org/0000-0002-4489-5753"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Najim Dehak","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6199","last_page":"6203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9987000226974487,"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":0.9973000288009644,"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":0.8262639045715332},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8005079030990601},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7851792573928833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6294412612915039},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.6231766939163208},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5468541979789734},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4824579358100891},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4556137025356293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3704811632633209},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36333492398262024},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3289753794670105}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8262639045715332},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8005079030990601},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7851792573928833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6294412612915039},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.6231766939163208},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5468541979789734},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4824579358100891},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4556137025356293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3704811632633209},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36333492398262024},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3289753794670105},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8461673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1590235378","https://openalex.org/W1612003148","https://openalex.org/W1964155876","https://openalex.org/W1998808035","https://openalex.org/W2100002341","https://openalex.org/W2120615054","https://openalex.org/W2149684865","https://openalex.org/W2157364932","https://openalex.org/W2168363555","https://openalex.org/W2238728730","https://openalex.org/W2262907013","https://openalex.org/W2518058337","https://openalex.org/W2558960030","https://openalex.org/W2587150483","https://openalex.org/W2616922365","https://openalex.org/W2951903140","https://openalex.org/W2963083845","https://openalex.org/W2963514026","https://openalex.org/W2963921497","https://openalex.org/W4231510805","https://openalex.org/W6636440780","https://openalex.org/W6674813771","https://openalex.org/W6683390034","https://openalex.org/W6689951360","https://openalex.org/W6692924172"],"related_works":["https://openalex.org/W2151749779","https://openalex.org/W3179968364","https://openalex.org/W1999612375","https://openalex.org/W2938107654","https://openalex.org/W3196421258","https://openalex.org/W4387301579","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2763956190","https://openalex.org/W4239306820"],"abstract_inverted_index":{"We":[0,66,78],"present":[1],"an":[2],"end-to-end":[3],"multi-scale":[4],"Convolutional":[5],"Neural":[6],"Network":[7],"(CNN)":[8],"framework":[9,69],"for":[10,23],"topic":[11,53],"identification":[12,47,64],"(topic":[13],"ID).":[14],"In":[15],"this":[16,57],"work,":[17],"we":[18,59],"examined":[19,50],"multi":[20],"-scale":[21],"CNN":[22],"classification":[24],"using":[25,37],"raw":[26],"text":[27],"input.":[28],"Topical":[29],"word":[30],"embeddings":[31],"are":[32,94],"learnt":[33],"at":[34,102],"multiple":[35],"scales":[36],"parallel":[38],"convolutional":[39],"layers.":[40],"A":[41],"technique":[42],"to":[43,51,90],"integrate":[44],"verification":[45],"and":[46,76,84],"objectives":[48],"is":[49],"improve":[52],"ID":[54],"performance.":[55],"With":[56],"approach,":[58],"achieved":[60],"significant":[61],"improvement":[62],"in":[63],"task.":[65],"evaluated":[67],"our":[68,91],"on":[70,82,86,99],"two":[71],"contrasting":[72],"datasets:":[73],"20":[74,87],"newsgroups":[75],"Fisher.":[77],"obtained":[79],"92.93%":[80],"accuracy":[81],"Fisher":[83],"86.12%":[85],"newsgroups,":[88],"which":[89],"know":[92],"ledge":[93],"the":[95,103],"best":[96],"published":[97],"results":[98],"these":[100],"datasets":[101],"moment.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}