{"id":"https://openalex.org/W1987906472","doi":"https://doi.org/10.1007/s10115-011-0387-3","title":"A high-performing comprehensive learning algorithm for text classification without pre-labeled training set","display_name":"A high-performing comprehensive learning algorithm for text classification without pre-labeled training set","publication_year":2011,"publication_date":"2011-03-29","ids":{"openalex":"https://openalex.org/W1987906472","doi":"https://doi.org/10.1007/s10115-011-0387-3","mag":"1987906472"},"language":"en","primary_location":{"id":"doi:10.1007/s10115-011-0387-3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10115-011-0387-3","pdf_url":null,"source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","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/A5101626332","display_name":"Lizhen Liu","orcid":"https://orcid.org/0009-0008-3836-9571"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhen Liu","raw_affiliation_strings":["Information Engineering College, Capital Normal University, Beijing, People\u2019s Republic of China","Capital Normal University, Information Engineering College, Beijing, People\u2019s Republic of China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering College, Capital Normal University, Beijing, People\u2019s Republic of China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Capital Normal University, Information Engineering College, Beijing, People\u2019s Republic of China#TAB#","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039977424","display_name":"Qianhui Liang","orcid":"https://orcid.org/0000-0002-1703-9863"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Qianhui Liang","raw_affiliation_strings":["HP Labs, Singapore, Singapore","HP Labs, Singapore, Singapore#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Labs, Singapore, Singapore","institution_ids":[]},{"raw_affiliation_string":"HP Labs, Singapore, Singapore#TAB#","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5039977424"],"corresponding_institution_ids":[],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":null,"fwci":3.2023,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.92112082,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"29","issue":"3","first_page":"727","last_page":"738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9965000152587891,"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":0.9965000152587891,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9901999831199646,"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":0.9674999713897705,"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":0.6389393210411072},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6188373565673828},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.6091461777687073},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5889431238174438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.558434247970581},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.502755880355835},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.483218789100647},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46428433060646057},{"id":"https://openalex.org/keywords/co-training","display_name":"Co-training","score":0.4424092173576355},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.42141789197921753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4015074372291565},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.40089207887649536},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36619436740875244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33277058601379395},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28325155377388},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.12164884805679321}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6389393210411072},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6188373565673828},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.6091461777687073},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5889431238174438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.558434247970581},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.502755880355835},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.483218789100647},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46428433060646057},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.4424092173576355},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.42141789197921753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4015074372291565},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.40089207887649536},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36619436740875244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33277058601379395},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28325155377388},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.12164884805679321},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10115-011-0387-3","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10115-011-0387-3","pdf_url":null,"source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W25636905","https://openalex.org/W1479807131","https://openalex.org/W1506468943","https://openalex.org/W1556061037","https://openalex.org/W1564512069","https://openalex.org/W1569914580","https://openalex.org/W1625750137","https://openalex.org/W1817561967","https://openalex.org/W1984545377","https://openalex.org/W1994215021","https://openalex.org/W2005386510","https://openalex.org/W2012470703","https://openalex.org/W2040810017","https://openalex.org/W2077679384","https://openalex.org/W2083870627","https://openalex.org/W2093633881","https://openalex.org/W2105210239","https://openalex.org/W2105536892","https://openalex.org/W2113051562","https://openalex.org/W2121852483","https://openalex.org/W2125753551","https://openalex.org/W2137686028","https://openalex.org/W2157964153","https://openalex.org/W2158866759","https://openalex.org/W2160838274","https://openalex.org/W2319224732","https://openalex.org/W2325607637","https://openalex.org/W2359088290","https://openalex.org/W2361043606","https://openalex.org/W2364882444","https://openalex.org/W2394699733","https://openalex.org/W2475662054","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2186473728","https://openalex.org/W2098708659","https://openalex.org/W2368299322","https://openalex.org/W2133556223","https://openalex.org/W2382572377","https://openalex.org/W1520691178","https://openalex.org/W2184770606","https://openalex.org/W57680428","https://openalex.org/W2126514932","https://openalex.org/W4205524645"],"abstract_inverted_index":null,"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}