{"id":"https://openalex.org/W2399391986","doi":"https://doi.org/10.5220/0004810500480059","title":"On Selecting Helpful Unlabeled Data for Improving Semi-Supervised Support Vector Machines","display_name":"On Selecting Helpful Unlabeled Data for Improving Semi-Supervised Support Vector Machines","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2399391986","doi":"https://doi.org/10.5220/0004810500480059","mag":"2399391986"},"language":"en","primary_location":{"id":"doi:10.5220/0004810500480059","is_oa":false,"landing_page_url":"https://doi.org/10.5220/0004810500480059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods","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":[],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.44894316,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.86700917,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"59"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9919999837875366,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9919999837875366,"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":0.9417999982833862,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6920648813247681},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6516427993774414},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6499091386795044},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5781735181808472},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5762441158294678},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5644344687461853},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5538750290870667},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5427148938179016},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5408305525779724},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.42199257016181946},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3530959486961365}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6920648813247681},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6516427993774414},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6499091386795044},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5781735181808472},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5762441158294678},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5644344687461853},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5538750290870667},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5427148938179016},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5408305525779724},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.42199257016181946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3530959486961365}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0004810500480059","is_oa":false,"landing_page_url":"https://doi.org/10.5220/0004810500480059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385484789","https://openalex.org/W2924161931","https://openalex.org/W1977678056","https://openalex.org/W3204418343","https://openalex.org/W2365028544","https://openalex.org/W2894446834","https://openalex.org/W1560624709","https://openalex.org/W4309984931","https://openalex.org/W4300028754","https://openalex.org/W2019288156"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"have":[2,60,174],"demonstrated":[3],"that":[4,9,23,34,140,173,202],"semi-supervised":[5,123],"learning":[6],"(SSL)":[7],"approaches":[8],"use":[10,24],"both":[11],"labeled":[12,26,183],"and":[13,19,77,197],"unlabeled":[14,36,55,107,164,171],"data":[15,37,165],"are":[16,109,166,177],"more":[17],"effective":[18],"robust":[20],"than":[21],"those":[22],"only":[25,89],"data.":[27],"However,":[28,84],"it":[29,99],"is":[30,38,68,88,131,135],"also":[31],"well":[32],"known":[33],"using":[35,128,153,195],"not":[39,101],"always":[40],"helpful":[41,54],"in":[42,46,63,142,225],"SSL":[43],"algorithms.":[44],"Thus,":[45],"order":[47,114],"to":[48,115,146],"select":[49],"a":[50,119,136],"small":[51],"amount":[52],"of":[53,121,139,149,162,211,227],"samples,":[56,97],"various":[57],"selection":[58,129],"criteria":[59],"been":[61],"proposed":[62,204],"the":[64,71,78,86,92,96,106,111,147,150,154,159,163,182,188,203,209,212],"literature.":[65],"One":[66],"criterion":[67,87,130],"based":[69],"on":[70],"prediction":[72],"by":[73],"an":[74],"ensemble":[75,189],"classifier":[76],"similarity":[79],"between":[80],"pairwise":[81],"training":[82,122],"samples.":[83],"because":[85],"concerned":[90],"with":[91,181,217],"distance":[93],"information":[94],"among":[95],"sometimes":[98],"does":[100],"work":[102],"appropriately,":[103],"particularly":[104],"when":[105],"samples":[108,172],"near":[110],"boundary.":[112],"In":[113,144],"address":[116],"this":[117,133],"concern,":[118],"method":[120,134],"support":[124],"vector":[125],"machines":[126],"(S3VMs)":[127],"investigated;":[132],"modified":[137],"version":[138],"used":[141,185],"SemiBoost.":[143],"addition":[145],"quantities":[148],"original":[151],"criterion,":[152],"estimated":[155],"conditional":[156],"class":[157],"probability,":[158],"confidence":[160],"values":[161],"computed":[167],"first.":[168],"Then,":[169],"some":[170],"higher":[175],"confidences":[176],"selected":[178],"and,":[179,215],"together":[180],"data,":[184],"for":[186,208],"retraining":[187],"classifier.":[190],"The":[191],"experimental":[192],"results,":[193],"obtained":[194],"artificial":[196],"real-life":[198],"benchmark":[199],"datasets,":[200],"demonstrate":[201],"mechanism":[205],"can":[206,220],"compensate":[207],"shortcomings":[210],"traditional":[213],"S3VMs":[214],"compared":[216],"previous":[218],"approaches,":[219],"achieve":[221],"further":[222],"improved":[223],"results":[224],"terms":[226],"classification":[228],"accuracy.":[229]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}