{"id":"https://openalex.org/W2378145258","doi":null,"title":"Incremental Learning Algorithm Based on Support Vector Machine","display_name":"Incremental Learning Algorithm Based on Support Vector Machine","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2378145258","mag":"2378145258"},"language":"en","primary_location":{"id":"mag:2378145258","doi":null,"is_oa":false,"landing_page_url":"https://en.cnki.com.cn/Article_en/CJFDTOTAL-JLDX201003026.htm","pdf_url":null,"source":{"id":"https://openalex.org/S4306515714","display_name":"Journal of Jilin University(Science Edition)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Jilin University(Science Edition)","raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5005702411","display_name":"Guan Wei-zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guan Wei-zhou","raw_affiliation_strings":["School of Computer Science and Information Technology , Northeast Normal University , Changchun , 130117 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Technology , Northeast Normal University , Changchun , 130117 , China","institution_ids":["https://openalex.org/I184983240"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005702411"],"corresponding_institution_ids":["https://openalex.org/I184983240"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.3644999861717224,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.3644999861717224,"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/T12676","display_name":"Machine Learning and ELM","score":0.2919999957084656,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.16300000250339508,"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/incremental-learning","display_name":"incremental learning","score":0.9919999837875366},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9800000190734863},{"id":"https://openalex.org/keywords/karush-kuhn-tucker-conditions","display_name":"Karush-Kuhn-Tucker conditions","score":0.8309999704360962}],"concepts":[{"id":"https://openalex.org/C50454189","wikidata":"https://www.wikidata.org/wiki/Q2075125","display_name":"Karush\u2013Kuhn\u2013Tucker conditions","level":2,"score":0.9480335712432861},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7627108097076416},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5428211688995361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5306298732757568},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5220969915390015},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5079165101051331},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.4446038603782654},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44249486923217773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4297051429748535},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4213976562023163},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.4139624834060669},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40483346581459045},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39970454573631287},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34706780314445496},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.17211925983428955},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2378145258","doi":null,"is_oa":false,"landing_page_url":"https://en.cnki.com.cn/Article_en/CJFDTOTAL-JLDX201003026.htm","pdf_url":null,"source":{"id":"https://openalex.org/S4306515714","display_name":"Journal of Jilin University(Science Edition)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Jilin University(Science Edition)","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2097061078","https://openalex.org/W2394429694","https://openalex.org/W2134882467","https://openalex.org/W2366723122","https://openalex.org/W2151306933","https://openalex.org/W2354023007","https://openalex.org/W2374634713","https://openalex.org/W2362003519","https://openalex.org/W2959687533","https://openalex.org/W2348364718"],"abstract_inverted_index":{"The":[0],"relationship":[1],"between":[2],"KKT":[3,44],"conditions":[4,45],"and":[5,9,71,87,104],"the":[6,10,13,19,25,29,43,49,60,64,69,72,75,90,94,100],"studied":[7],"sample":[8,92],"analysis":[11],"of":[12,15,21,31,62,77,93],"change":[14],"support":[16],"vector":[17],"after":[18,82],"addition":[20],"incremental":[22,38,91],"samples":[23,51],"to":[24,42],"training":[26,84],"set":[27,81],"on":[28,36,68],"basis":[30],"an":[32],"improved":[33],"Upper":[34],"Limit":[35],"Increment":[37],"learning":[39],"algorithm.":[40],"According":[41],"for":[46],"this":[47],"algorithm":[48,101],"corresponding":[50],"were":[52],"divided":[53],"into":[54],"three":[55],"categories:the":[56],"RIG":[57],"distributed":[58],"outside":[59],"interval":[61],"classifier;":[63],"MAR":[65],"at":[66],"intervals":[67,76],"classification":[70],"ERR":[73,80],"inside":[74],"classification.":[78],"And":[79],"each":[83],"was":[85],"preserved":[86],"combined":[88],"with":[89],"next":[95],"training.":[96],"Experiments":[97],"show":[98],"that":[99],"is":[102],"feasible":[103],"effective.":[105]},"counts_by_year":[],"updated_date":"2025-10-10T17:16:08.811792","created_date":"2016-06-24T00:00:00"}
