{"id":"https://openalex.org/W7131123572","doi":"https://doi.org/10.1016/j.neucom.2026.133130","title":"Improving short text clustering through hybrid augmentation and contrastive learning","display_name":"Improving short text clustering through hybrid augmentation and contrastive learning","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131123572","doi":"https://doi.org/10.1016/j.neucom.2026.133130"},"language":"en","primary_location":{"id":"doi:10.1016/j.neucom.2026.133130","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neucom.2026.133130","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.neucom.2026.133130","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126629734","display_name":"Weizhen Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weizhen Zhang","raw_affiliation_strings":["School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China","institution_ids":["https://openalex.org/I39774598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126659068","display_name":"Xiaoxuan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoxuan Wu","raw_affiliation_strings":["School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China","institution_ids":["https://openalex.org/I39774598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126612864","display_name":"Mengnan Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengnan Zhou","raw_affiliation_strings":["School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China","institution_ids":["https://openalex.org/I39774598"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069351435","display_name":"Rui Guan","orcid":"https://orcid.org/0000-0002-4140-0030"},"institutions":[{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Guan","raw_affiliation_strings":["School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Big Data, Hefei University, Hefei, Anhui, China","institution_ids":["https://openalex.org/I39774598"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126659068"],"corresponding_institution_ids":["https://openalex.org/I39774598"],"apc_list":{"value":2470,"currency":"USD","value_usd":2470},"apc_paid":{"value":2470,"currency":"USD","value_usd":2470},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87631138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"677","issue":null,"first_page":"133130","last_page":"133130"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.07769999653100967,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.07769999653100967,"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":0.07500000298023224,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0632999986410141,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8744999766349792},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6938999891281128},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4494999945163727},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4239000082015991},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.3937000036239624},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3725000023841858},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.36010000109672546},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.33869999647140503}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8744999766349792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8008999824523926},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6938999891281128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6136999726295471},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4494999945163727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.3937000036239624},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3919000029563904},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3725000023841858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37220001220703125},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.33869999647140503},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.32919999957084656},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.3160000145435333},{"id":"https://openalex.org/C39235581","wikidata":"https://www.wikidata.org/wiki/Q5158434","display_name":"Conceptual clustering","level":5,"score":0.30390000343322754},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C3018790387","wikidata":"https://www.wikidata.org/wiki/Q869010","display_name":"Hybrid learning","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.26600000262260437},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.neucom.2026.133130","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neucom.2026.133130","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.neucom.2026.133130","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neucom.2026.133130","pdf_url":null,"source":{"id":"https://openalex.org/S45693802","display_name":"Neurocomputing","issn_l":"0925-2312","issn":["0925-2312","1872-8286"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neurocomputing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6756170988082886,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W107619411","https://openalex.org/W2100495367","https://openalex.org/W2112796928","https://openalex.org/W2442340835","https://openalex.org/W2576754561","https://openalex.org/W2741943936","https://openalex.org/W2949128310","https://openalex.org/W2963545917","https://openalex.org/W2971296908","https://openalex.org/W3156636935","https://openalex.org/W3162391496","https://openalex.org/W3176108833","https://openalex.org/W3196750896","https://openalex.org/W3198659451","https://openalex.org/W4231029117","https://openalex.org/W4322504919","https://openalex.org/W4393153153"],"related_works":[],"abstract_inverted_index":{"Short":[0],"text":[1,49,133,153],"clustering":[2,22,32,50,120,125,134,194],"presents":[3],"significant":[4],"challenges":[5],"due":[6],"to":[7,18,28,61,97,106,139],"the":[8,12,25,63,98,103,131,137,156,183,188],"inherent":[9],"characteristics":[10],"of":[11,74,92],"data,":[13,100],"which":[14],"are":[15,34],"highly":[16],"susceptible":[17],"noise,":[19],"thereby":[20,101],"impacting":[21],"results.":[23],"Enhancing":[24],"model's":[26,64],"robustness":[27,190],"noise":[29],"and":[30,58,81,94,155,172,191],"improving":[31],"performance":[33,149],"crucial":[35],"issues":[36],"in":[37],"this":[38],"area.":[39],"To":[40],"address":[41],"these":[42],"challenges,":[43],"we":[44,112],"propose":[45],"a":[46,90,114],"novel":[47],"short":[48,132,152],"model":[51,138],"(SCHACL)":[52],"that":[53,160,182],"combines":[54],"hybrid":[55,78,85],"data":[56,79,86,116,144],"augmentation":[57,80,87,117],"contrastive":[59,82,124,128],"learning":[60,129],"improve":[62],"robustness,":[65],"particularly":[66],"when":[67],"dealing":[68],"with":[69],"noisy":[70,108],"data.":[71,109],"SCHACL":[72,161],"consists":[73],"two":[75],"key":[76],"modules:":[77],"clustering.":[83],"The":[84,123],"module":[88,126],"applies":[89],"mix":[91],"strong":[93],"weak":[95],"augmentations":[96],"original":[99],"enhancing":[102],"model\u2019s":[104,189],"ability":[105],"handle":[107],"In":[110],"addition,":[111],"introduce":[113],"new":[115],"technique":[118],"for":[119],"tasks\u2014Pos-based":[121],"Deletion.":[122],"integrates":[127],"into":[130],"process,":[135],"enabling":[136],"better":[140],"differentiate":[141],"between":[142],"distinct":[143],"clusters.":[145],"We":[146],"evaluate":[147],"SCHACL\u2019s":[148],"on":[150],"eight":[151],"datasets,":[154],"experimental":[157],"results":[158,180],"demonstrate":[159],"significantly":[162,192],"outperforms":[163],"several":[164],"baseline":[165],"models.":[166],"Specifically,":[167],"accuracy":[168],"improves":[169,193],"by":[170,177],"0.72%-4.16%,":[171],"normalized":[173],"mutual":[174],"information":[175],"increases":[176],"0.27%-2.68%.":[178],"These":[179],"confirm":[181],"proposed":[184],"approach":[185],"effectively":[186],"enhances":[187],"performance.":[195]},"counts_by_year":[],"updated_date":"2026-02-27T06:17:20.405678","created_date":"2026-02-24T00:00:00"}