{"id":"https://openalex.org/W2586956264","doi":"https://doi.org/10.1109/smc.2016.7844572","title":"Semi-supervised learning using higher-order co-occurrence paths to overcome the complexity of data representation","display_name":"Semi-supervised learning using higher-order co-occurrence paths to overcome the complexity of data representation","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2586956264","doi":"https://doi.org/10.1109/smc.2016.7844572","mag":"2586956264"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2016.7844572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5056971742","display_name":"Murat Can Ganiz","orcid":"https://orcid.org/0000-0001-8338-991X"},"institutions":[{"id":"https://openalex.org/I74897591","display_name":"Marmara University","ror":"https://ror.org/02kswqa67","country_code":"TR","type":"education","lineage":["https://openalex.org/I74897591"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Murat Can Ganiz","raw_affiliation_strings":["Computer Engineering Department, Marmara University, \u0130stanbul, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, Marmara University, \u0130stanbul, Turkey","institution_ids":["https://openalex.org/I74897591"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5056971742"],"corresponding_institution_ids":["https://openalex.org/I74897591"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.16997839,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"002242","last_page":"002247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","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/T12535","display_name":"Machine Learning and Data Classification","score":0.9848999977111816,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7298651337623596},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6827972531318665},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6607449054718018},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.6191821098327637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.616584837436676},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5820285081863403},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5777136087417603},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5278006792068481},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5182763934135437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45588740706443787},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42017364501953125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3321853578090668},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16453048586845398}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7298651337623596},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6827972531318665},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6607449054718018},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.6191821098327637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.616584837436676},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5820285081863403},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5777136087417603},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5278006792068481},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5182763934135437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45588740706443787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42017364501953125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3321853578090668},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16453048586845398},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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":2,"locations":[{"id":"doi:10.1109/smc.2016.7844572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"pmh:oai:openaccess.marmara.edu.tr:11424/247826","is_oa":false,"landing_page_url":"https://hdl.handle.net/11424/247826","pdf_url":null,"source":{"id":"https://openalex.org/S4306401380","display_name":"Dspace Repository (Marmara \u00dcniversitesi)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I74897591","host_organization_name":"Marmara University","host_organization_lineage":["https://openalex.org/I74897591"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320325078","display_name":"Marmara \u00dcniversitesi","ror":"https://ror.org/02kswqa67"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W41690797","https://openalex.org/W97949734","https://openalex.org/W137112649","https://openalex.org/W1479807131","https://openalex.org/W1550206324","https://openalex.org/W1553187123","https://openalex.org/W1969198379","https://openalex.org/W2017102965","https://openalex.org/W2070780210","https://openalex.org/W2076280956","https://openalex.org/W2104290444","https://openalex.org/W2113532220","https://openalex.org/W2114524997","https://openalex.org/W2115477592","https://openalex.org/W2131904442","https://openalex.org/W2135725275","https://openalex.org/W2136504847","https://openalex.org/W2140336868","https://openalex.org/W2147152072","https://openalex.org/W2155342973","https://openalex.org/W2164810648","https://openalex.org/W2247407167","https://openalex.org/W2486125749","https://openalex.org/W2920725015","https://openalex.org/W2962735828","https://openalex.org/W2997701990","https://openalex.org/W3146227918","https://openalex.org/W3148472308","https://openalex.org/W6632865047","https://openalex.org/W6633115214","https://openalex.org/W6675747103","https://openalex.org/W6680140577","https://openalex.org/W6680642335","https://openalex.org/W6681046083","https://openalex.org/W6738379573"],"related_works":["https://openalex.org/W4226363941","https://openalex.org/W34092691","https://openalex.org/W2365028544","https://openalex.org/W4309984931","https://openalex.org/W4282977123","https://openalex.org/W2186210338","https://openalex.org/W4206276646","https://openalex.org/W2371815184","https://openalex.org/W1571801203","https://openalex.org/W2369040532"],"abstract_inverted_index":{"We":[0,19,135],"present":[1],"a":[2,35,84],"novel":[3],"approach":[4,109],"to":[5,56,68,75,102],"semi-supervised":[6],"learning":[7],"for":[8,94,115],"text":[9],"classification":[10,150],"based":[11,38],"on":[12,34],"the":[13,21,66,76,95,104,116,123,128,132,143,149,154,157],"higher-order":[14,50],"co-occurrence":[15,51],"paths":[16,52],"of":[17,41,89,125,156],"words.":[18],"name":[20],"proposed":[22,64,108],"method":[23],"as":[24],"Semi-Supervised":[25],"Semantic":[26],"Higher-Order":[27],"Smoothing":[28],"(S3HOS).":[29],"The":[30,107],"S3HOS":[31,139],"is":[32,160,165],"built":[33],"tri-partite":[36],"graph":[37],"data":[39,159,164],"representation":[40],"labeled":[42,73,129,158],"and":[43,86,121,146],"unlabeled":[44,77,98,119,163],"documents":[45,74,99,105,120,130],"that":[46,138],"allows":[47,110],"semantics":[48],"in":[49,65,97,118,127],"between":[53],"terms":[54,96,117,126],"(words)":[55],"be":[57],"exploited.":[58],"There":[59],"are":[60],"several":[61],"graph-based":[62],"techniques":[63],"literature":[67],"diffuse":[69],"class":[70,91,112],"labels":[71],"from":[72],"documents.":[78],"In":[79],"this":[80],"study":[81],"we":[82],"propose":[83],"different":[85],"natural":[87],"way":[88],"estimating":[90,111],"conditional":[92,113],"probabilities":[93,114],"without":[100],"need":[101],"label":[103],"first.":[106],"improve":[122,142],"estimation":[124,145],"at":[131],"same":[133],"time.":[134],"experimentally":[136],"show":[137],"can":[140],"highly":[141],"parameter":[144],"hence":[147],"increase":[148],"accuracy":[151],"particularly":[152],"when":[153],"amount":[155],"scarce":[161],"but":[162],"plentiful.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}