{"id":"https://openalex.org/W3003321296","doi":"https://doi.org/10.1109/globalsip45357.2019.8969462","title":"A Domain Knowledge\u2014Enabled Hybrid Semi-Supervision Learning Method","display_name":"A Domain Knowledge\u2014Enabled Hybrid Semi-Supervision Learning Method","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3003321296","doi":"https://doi.org/10.1109/globalsip45357.2019.8969462","mag":"3003321296"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip45357.2019.8969462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip45357.2019.8969462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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/A5029720510","display_name":"Yifu Wu","orcid":"https://orcid.org/0000-0001-5132-2980"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yifu Wu","raw_affiliation_strings":["Dept of Computer and Information Technology, Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Dept of Computer and Information Technology, Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038987597","display_name":"Jin Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Wei","raw_affiliation_strings":["Dept of Computer and Information Technology, Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Dept of Computer and Information Technology, Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012276219","display_name":"Rigoberto Roche","orcid":null},"institutions":[{"id":"https://openalex.org/I2799786008","display_name":"Glenn Research Center","ror":"https://ror.org/059fqnc42","country_code":"US","type":"facility","lineage":["https://openalex.org/I2799786008","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rigoberto Roche'","raw_affiliation_strings":["NASA Glenn Research Center, Cleveland, USA"],"affiliations":[{"raw_affiliation_string":"NASA Glenn Research Center, Cleveland, USA","institution_ids":["https://openalex.org/I2799786008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029720510"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18643105,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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":0.9986000061035156,"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":0.9983999729156494,"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":0.8546421527862549},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7984610199928284},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6372442245483398},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5661346912384033},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5593535304069519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.54848313331604},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5236625075340271},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4730081856250763}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8546421527862549},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7984610199928284},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6372442245483398},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5661346912384033},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5593535304069519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.54848313331604},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5236625075340271},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4730081856250763},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globalsip45357.2019.8969462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip45357.2019.8969462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","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":30,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W830076066","https://openalex.org/W1983320747","https://openalex.org/W2095705004","https://openalex.org/W2129068307","https://openalex.org/W2154368244","https://openalex.org/W2311110368","https://openalex.org/W2530816535","https://openalex.org/W2592691248","https://openalex.org/W2746791238","https://openalex.org/W2786304948","https://openalex.org/W2810565934","https://openalex.org/W2914331073","https://openalex.org/W2950757414","https://openalex.org/W2951970475","https://openalex.org/W2952229419","https://openalex.org/W2953070460","https://openalex.org/W2963019788","https://openalex.org/W2963687836","https://openalex.org/W3010865323","https://openalex.org/W3137197540","https://openalex.org/W4206723194","https://openalex.org/W6600213771","https://openalex.org/W6623329352","https://openalex.org/W6674330103","https://openalex.org/W6678975374","https://openalex.org/W6682991711","https://openalex.org/W6733814495","https://openalex.org/W6753195712","https://openalex.org/W6764051988"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W1583422155","https://openalex.org/W1649619740","https://openalex.org/W3213252596","https://openalex.org/W1534006406"],"abstract_inverted_index":{"Due":[0],"to":[1,16,85],"the":[2,25,38,45,81,87,92,101],"advances":[3],"in":[4,20,65,91],"dramatically":[5],"increased":[6],"computing":[7,72],"power,":[8],"machine":[9,32,77],"learning":[10,33],"technologies":[11,34],"have":[12],"been":[13],"widely":[14],"exploited":[15],"provide":[17],"promising":[18],"solutions":[19],"different":[21],"application":[22],"fields.":[23],"However,":[24],"high":[26],"performance":[27],"of":[28,30,40,94,103],"many":[29],"these":[31],"highly":[35],"relies":[36],"on":[37],"availability":[39],"sufficient":[41],"annotated":[42],"data.":[43,97],"Considering":[44],"fact":[46],"that":[47,79],"data":[48],"annotation":[49],"is":[50,57],"an":[51],"extremely":[52],"time-consuming":[53],"process,":[54],"this":[55,63,66],"condition":[56],"not":[58],"always":[59],"practical.":[60],"To":[61],"address":[62],"challenge,":[64],"paper":[67],"we":[68],"propose":[69],"a":[70],"novel":[71],"method,":[73],"called":[74],"hybrid":[75],"semi-supervision":[76],"learning,":[78],"exploits":[80],"loose":[82],"domain":[83],"knowledge":[84],"enable":[86],"accurate":[88],"results":[89,99],"even":[90],"presence":[93],"limited":[95],"labeled":[96],"Simulations":[98],"illustrate":[100],"effectiveness":[102],"our":[104],"method.":[105]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
