{"id":"https://openalex.org/W1992916781","doi":"https://doi.org/10.1109/nlpke.2010.5587844","title":"Feature selection for Chinese Text Categorization based on improved particle swarm optimization","display_name":"Feature selection for Chinese Text Categorization based on improved particle swarm optimization","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W1992916781","doi":"https://doi.org/10.1109/nlpke.2010.5587844","mag":"1992916781"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2010.5587844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2010.5587844","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","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/A5100825764","display_name":"Yaohong Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaohong Jin","raw_affiliation_strings":["Institute of Chinese Information Processing, Beijing Normal University, Beijing, China","Institute of Chinese Information Processing, Beijing Normal University 100875, CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Chinese Information Processing, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Institute of Chinese Information Processing, Beijing Normal University 100875, CHINA","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101835518","display_name":"Wen Xiong","orcid":"https://orcid.org/0000-0003-1930-0049"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Xiong","raw_affiliation_strings":["School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China","School of computer science and technology, Beijing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of computer science and technology, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101811814","display_name":"Cong Wang","orcid":"https://orcid.org/0000-0002-2504-4056"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Wang","raw_affiliation_strings":["School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China","School of computer science and technology, Beijing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"School of computer science and technology, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5449,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.61848236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9943000078201294,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9943000078201294,"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":0.9926999807357788,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9682000279426575,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.701759934425354},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6949505805969238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6462458968162537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6377244591712952},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6278839111328125},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5728195905685425},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5357685685157776},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5075101256370544},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.4551955461502075},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4529430568218231},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.44637733697891235},{"id":"https://openalex.org/keywords/text-categorization","display_name":"Text categorization","score":0.4461367428302765},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.43629738688468933},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4337999224662781},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25060462951660156},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20227324962615967}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.701759934425354},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6949505805969238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6462458968162537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6377244591712952},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6278839111328125},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5728195905685425},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5357685685157776},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5075101256370544},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.4551955461502075},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4529430568218231},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.44637733697891235},{"id":"https://openalex.org/C2986744138","wikidata":"https://www.wikidata.org/wiki/Q302088","display_name":"Text categorization","level":3,"score":0.4461367428302765},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.43629738688468933},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4337999224662781},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25060462951660156},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20227324962615967},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nlpke.2010.5587844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2010.5587844","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5899999737739563,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1963626514","https://openalex.org/W1978394996","https://openalex.org/W2041145971","https://openalex.org/W2059115408","https://openalex.org/W2114569237","https://openalex.org/W2118020653","https://openalex.org/W2144301395","https://openalex.org/W2148603752","https://openalex.org/W2152195021","https://openalex.org/W2153635508","https://openalex.org/W2325227998","https://openalex.org/W2380724458","https://openalex.org/W2435251607","https://openalex.org/W2534020605","https://openalex.org/W2541768999","https://openalex.org/W3120421331","https://openalex.org/W6660731769","https://openalex.org/W6717827561","https://openalex.org/W6729051163"],"related_works":["https://openalex.org/W2360898036","https://openalex.org/W2390857744","https://openalex.org/W2133651098","https://openalex.org/W2390698788","https://openalex.org/W2078570174","https://openalex.org/W20047544","https://openalex.org/W2383063829","https://openalex.org/W2138922887","https://openalex.org/W2082678934","https://openalex.org/W2111353337"],"abstract_inverted_index":{"Feature":[0],"selection":[1,55],"is":[2,33,65],"an":[3,126],"important":[4],"preprocessing":[5],"step":[6],"of":[7,39,80,100],"Chinese":[8,58,107,139],"Text":[9,108],"Categorization,":[10],"which":[11,35,67],"reduces":[12],"the":[13,18,37,78,95,98,119,134],"high":[14],"dimension":[15],"and":[16,47,51,84,93,125],"keeps":[17],"reduced":[19],"results":[20,79],"comprehensible":[21],"compared":[22],"to":[23,29,73,89],"feature":[24,54,91,128],"extraction.":[25],"A":[26],"novel":[27,135],"criterion":[28,121],"filter":[30],"features":[31,75,123],"coarsely":[32],"proposed,":[34],"integrating":[36],"superiorities":[38],"term":[40],"frequency-inverse":[41],"document":[42],"frequency":[43],"as":[44,49,97],"inner-class":[45],"measure":[46],"CHI-square":[48],"inter-class,":[50],"a":[52,112],"new":[53,120],"method":[56,137],"for":[57,122,138],"text":[59,140],"categorization":[60],"based":[61],"on":[62,77,104],"swarm":[63,71],"intelligence":[64],"presented,":[66],"using":[68,118],"improved":[69],"particle":[70],"optimization":[72],"select":[74],"fine":[76],"coarse":[81],"grain":[82],"filtering,":[83],"utilizing":[85,133],"support":[86],"vector":[87],"machine":[88],"evaluate":[90],"subsets":[92],"taking":[94],"evaluations":[96],"fitness":[99],"particles.":[101],"The":[102],"experiments":[103],"Fudan":[105],"University":[106],"Classification":[109],"Corpus":[110],"show":[111],"higher":[113],"classification":[114],"accuracy":[115],"obtained":[116],"by":[117,132],"filtering":[124],"effective":[127],"reduction":[129],"ratio":[130],"attained":[131],"FS":[136],"categorization.":[141]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}