{"id":"https://openalex.org/W4309065674","doi":"https://doi.org/10.1080/08839514.2022.2145637","title":"Intelligent Grouping Method of Science and Technology Projects Based on Data Augmentation and SMOTE","display_name":"Intelligent Grouping Method of Science and Technology Projects Based on Data Augmentation and SMOTE","publication_year":2022,"publication_date":"2022-11-15","ids":{"openalex":"https://openalex.org/W4309065674","doi":"https://doi.org/10.1080/08839514.2022.2145637"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2145637","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2145637","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/08839514.2022.2145637","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026785656","display_name":"Can Zhou","orcid":"https://orcid.org/0000-0002-2778-0022"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Zhou","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643013","display_name":"Mengting Li","orcid":"https://orcid.org/0000-0002-0144-870X"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengting Li","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064521142","display_name":"Sha Yu","orcid":"https://orcid.org/0000-0001-9796-1446"},"institutions":[{"id":"https://openalex.org/I4210094058","display_name":"State Administration of Foreign Exchange","ror":"https://ror.org/00phbja87","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210094058"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sha Yu","raw_affiliation_strings":["Special Management Department, China Science and Technology Exchange Center, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Special Management Department, China Science and Technology Exchange Center, Beijing, China","institution_ids":["https://openalex.org/I4210094058"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5064521142"],"corresponding_institution_ids":["https://openalex.org/I4210094058"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":0.2653,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6203906,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.992900013923645,"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":0.992900013923645,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9821000099182129,"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":0.9753999710083008,"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":0.8706969618797302},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.7376100420951843},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.654427707195282},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5675977468490601},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5661314129829407},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5081303119659424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4936131238937378},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44577786326408386}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8706969618797302},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.7376100420951843},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.654427707195282},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5675977468490601},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5661314129829407},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5081303119659424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4936131238937378},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44577786326408386},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2022.2145637","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2145637","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:da048aef6be44023abf0f073f8f1c0b7","is_oa":true,"landing_page_url":"https://doaj.org/article/da048aef6be44023abf0f073f8f1c0b7","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 36, Iss 1 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2145637","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2145637","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2053968437","https://openalex.org/W2096479318","https://openalex.org/W2118978333","https://openalex.org/W2148143831","https://openalex.org/W2250539671","https://openalex.org/W2295598076","https://openalex.org/W2559655401","https://openalex.org/W2574070988","https://openalex.org/W2580878117","https://openalex.org/W2604272474","https://openalex.org/W2612690371","https://openalex.org/W2886346335","https://openalex.org/W2892137778","https://openalex.org/W2898041880","https://openalex.org/W2898339904","https://openalex.org/W2913338690","https://openalex.org/W2914767245","https://openalex.org/W2961125888","https://openalex.org/W2963026768","https://openalex.org/W2969322340","https://openalex.org/W2971296908","https://openalex.org/W2972914098","https://openalex.org/W2990138404","https://openalex.org/W2991113277","https://openalex.org/W3000339128","https://openalex.org/W3002312850","https://openalex.org/W3006193056","https://openalex.org/W3035542229","https://openalex.org/W3037422790","https://openalex.org/W3081972231","https://openalex.org/W3097513514","https://openalex.org/W3121726600","https://openalex.org/W3122241445","https://openalex.org/W3132467470","https://openalex.org/W3159075545","https://openalex.org/W3159347382","https://openalex.org/W3176923149","https://openalex.org/W3180181113","https://openalex.org/W3184110467","https://openalex.org/W3201915713","https://openalex.org/W4205435066","https://openalex.org/W4206141129","https://openalex.org/W4239510810","https://openalex.org/W4251204862"],"related_works":["https://openalex.org/W2355927362","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4220909832","https://openalex.org/W3195168932","https://openalex.org/W1996541855","https://openalex.org/W4211165872","https://openalex.org/W3107602296","https://openalex.org/W2556319748","https://openalex.org/W3158784734"],"abstract_inverted_index":{"The":[0,88,147],"current":[1],"evaluation":[2],"of":[3,18,38,41,45,53,105,149,169],"science":[4,66],"and":[5,14,48,67,84,95,107,109,145,153,159],"technology":[6,68],"projects":[7,21,69],"is":[8,25,31],"mainly":[9],"completed":[10],"by":[11,81],"peer":[12],"review,":[13],"in":[15],"the":[16,35,49,75,85,103,112,132,141,156,160,167,170],"process":[17,119],"evaluation,":[19],"dividing":[20],"into":[22],"different":[23],"groups":[24],"a":[26],"crucial":[27],"step.":[28],"Project":[29],"grouping":[30,63,134],"challenging":[32],"due":[33],"to":[34,101,118,122],"small":[36,76],"amounts":[37],"data,":[39],"sparsity":[40],"features,":[42],"broad":[43],"range":[44],"subject":[46],"areas,":[47],"seriously":[50],"uneven":[51],"distribution":[52],"categories.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,115],"propose":[59],"an":[60],"intelligent":[61],"automatic":[62],"method":[64,144],"for":[65],"based":[70],"on":[71],"keywords.":[72],"We":[73],"expanded":[74],"dataset":[77],"with":[78],"samples":[79],"generated":[80],"Paraphrasing,":[82,150],"Mixup,":[83],"GPT3":[86],"model.":[87],"text":[89],"feature":[90],"extraction":[91],"techniques":[92],"TF-IDF,":[93,151],"Word2Vec,":[94],"TF-IDF":[96],"weighted":[97],"Word2Vec":[98],"were":[99],"utilized":[100],"pre-process":[102],"keywords":[104],"projects,":[106],"SVM":[108,152],"XGBoost":[110],"as":[111],"classifier.":[113],"Besides,":[114],"used":[116],"SMOTE":[117,154],"imbalanced":[120],"data":[121,142],"alleviate":[123],"model":[124],"bias":[125],"toward":[126],"minority":[127],"classes.":[128],"Experiments":[129],"show":[130],"that":[131],"project":[133],"accuracy":[135],"was":[136],"substantially":[137],"improved":[138],"after":[139],"introducing":[140],"augmentation":[143],"SMOTE.":[146],"combination":[148],"achieved":[155],"best":[157],"performance,":[158],"F1":[161],"score":[162],"reached":[163],"96.78%,":[164],"which":[165],"proves":[166],"feasibility":[168],"proposed":[171],"method.":[172]},"counts_by_year":[{"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"}
