{"id":"https://openalex.org/W2794006653","doi":"https://doi.org/10.3233/ida-163264","title":"Multi-label classification of documents using fine-grained weights and modified co-training","display_name":"Multi-label classification of documents using fine-grained weights and modified co-training","publication_year":2018,"publication_date":"2018-02-22","ids":{"openalex":"https://openalex.org/W2794006653","doi":"https://doi.org/10.3233/ida-163264","mag":"2794006653"},"language":"en","primary_location":{"id":"doi:10.3233/ida-163264","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-163264","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-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/A5072515962","display_name":"Chang\u2010Hwan Lee","orcid":"https://orcid.org/0000-0003-3221-1171"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chang-Hwan Lee","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5072515962"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.02819206,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"22","issue":"1","first_page":"103","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9995999932289124,"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":0.9995999932289124,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/training","display_name":"Training (meteorology)","score":0.6141597032546997},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5753503441810608},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39432623982429504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3735211491584778},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3607594966888428},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09786489605903625}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6141597032546997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5753503441810608},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39432623982429504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3735211491584778},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3607594966888428},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09786489605903625},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-163264","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-163264","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.5099999904632568,"display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W66588809","https://openalex.org/W1502772707","https://openalex.org/W1524416683","https://openalex.org/W1550206324","https://openalex.org/W1975299065","https://openalex.org/W1998839399","https://openalex.org/W2014566476","https://openalex.org/W2015292887","https://openalex.org/W2016799887","https://openalex.org/W2049487246","https://openalex.org/W2061351061","https://openalex.org/W2091961126","https://openalex.org/W2098768220","https://openalex.org/W2122672280","https://openalex.org/W2129026672","https://openalex.org/W2132826100","https://openalex.org/W2135813353","https://openalex.org/W2140336868","https://openalex.org/W2161824996","https://openalex.org/W2165238043","https://openalex.org/W2296540310","https://openalex.org/W4232706428","https://openalex.org/W6631445940","https://openalex.org/W6638622987","https://openalex.org/W6654114405","https://openalex.org/W6818006502"],"related_works":["https://openalex.org/W2357241418","https://openalex.org/W2086064646","https://openalex.org/W2119135658","https://openalex.org/W2115485936","https://openalex.org/W3022131925","https://openalex.org/W2033914206","https://openalex.org/W2146076056","https://openalex.org/W2349174110","https://openalex.org/W1597238586","https://openalex.org/W1536405386"],"abstract_inverted_index":{"This":[0],"paper":[1],"use":[2,18],"multinomial":[3],"nave":[4],"Bayes":[5],"to":[6,28],"improve":[7],"multi-label":[8],"classification":[9],"methods":[10],"in":[11],"a":[12,23],"number":[13],"of":[14,32],"ways.":[15],"First,":[16],"we":[17,37],"the":[19,30,33],"value":[20],"weighting":[21,26],"method,":[22,27],"new":[24],"fine-grained":[25],"calculate":[29],"weights":[31],"feature":[34],"values.":[35],"Second,":[36],"employ":[38]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
