{"id":"https://openalex.org/W2172193264","doi":"https://doi.org/10.1109/ijcnn.2004.1379914","title":"Linguistic feature extraction using independent component analysis","display_name":"Linguistic feature extraction using independent component analysis","publication_year":2005,"publication_date":"2005-02-22","ids":{"openalex":"https://openalex.org/W2172193264","doi":"https://doi.org/10.1109/ijcnn.2004.1379914","mag":"2172193264"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1379914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1379914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","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":[{"author_position":"first","author":{"id":"https://openalex.org/A5030983114","display_name":"Timo Honkela","orcid":"https://orcid.org/0000-0003-0917-2020"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"T. Honkela","raw_affiliation_strings":["Neural Networks Research Center Laboratory of Computer and Information Science, Helsinki University of Technology, Finland"],"affiliations":[{"raw_affiliation_string":"Neural Networks Research Center Laboratory of Computer and Information Science, Helsinki University of Technology, Finland","institution_ids":["https://openalex.org/I133731052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061498233","display_name":"Aapo Hyv\u00e4rinen","orcid":"https://orcid.org/0000-0002-5806-4432"},"institutions":[{"id":"https://openalex.org/I133731052","display_name":"University of Helsinki","ror":"https://ror.org/040af2s02","country_code":"FI","type":"education","lineage":["https://openalex.org/I133731052"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"A. Hyvarinen","raw_affiliation_strings":["HIIT Basic Research Unit Department of Computer Science, University of Helsinki, Finland"],"affiliations":[{"raw_affiliation_string":"HIIT Basic Research Unit Department of Computer Science, University of Helsinki, Finland","institution_ids":["https://openalex.org/I133731052"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030983114"],"corresponding_institution_ids":["https://openalex.org/I133731052"],"apc_list":null,"apc_paid":null,"fwci":5.5124,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.96397215,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"279","last_page":"284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9983999729156494,"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/T12946","display_name":"Fractal and DNA sequence analysis","score":0.9517999887466431,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8410931825637817},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7442519664764404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6298755407333374},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.6120952367782593},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5994659066200256},{"id":"https://openalex.org/keywords/semantic-analysis","display_name":"Semantic analysis (machine learning)","score":0.5173815488815308},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5039870142936707},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4944741725921631},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4784983694553375},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.4359130263328552},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42262542247772217},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.20326918363571167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8410931825637817},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7442519664764404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6298755407333374},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.6120952367782593},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5994659066200256},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.5173815488815308},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5039870142936707},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4944741725921631},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4784983694553375},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4359130263328552},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42262542247772217},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20326918363571167},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2004.1379914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1379914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1.2166","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2166","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.helsinki.fi/u/ahyvarin/papers/Honkela04.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W4930780","https://openalex.org/W44505322","https://openalex.org/W243270425","https://openalex.org/W1488854477","https://openalex.org/W1548802052","https://openalex.org/W1574901103","https://openalex.org/W1593045043","https://openalex.org/W1624376135","https://openalex.org/W1983578042","https://openalex.org/W1984565341","https://openalex.org/W1996355918","https://openalex.org/W1997379117","https://openalex.org/W2006077098","https://openalex.org/W2035238564","https://openalex.org/W2099741732","https://openalex.org/W2104897731","https://openalex.org/W2141224535","https://openalex.org/W2147152072","https://openalex.org/W2149671658","https://openalex.org/W2155602043","https://openalex.org/W2159637323","https://openalex.org/W2165612380","https://openalex.org/W2561277497","https://openalex.org/W3149550307","https://openalex.org/W4205778870","https://openalex.org/W4252434862","https://openalex.org/W6600179491","https://openalex.org/W6682745044"],"related_works":["https://openalex.org/W2013209066","https://openalex.org/W2080378089","https://openalex.org/W2977528137","https://openalex.org/W2921035136","https://openalex.org/W2786154338","https://openalex.org/W1964929739","https://openalex.org/W2005406133","https://openalex.org/W1690254038","https://openalex.org/W2024570182","https://openalex.org/W2367834105"],"abstract_inverted_index":{"Our":[0],"aim":[1],"is":[2,44],"to":[3,27,78],"find":[4],"syntactic":[5,93,133,174],"and":[6,38,99,134,149],"semantic":[7,36,42,100,135,176],"relationships":[8,86],"of":[9,15,21,51],"words":[10],"based":[11],"on":[12,124],"the":[13,19,85,96,103,118],"analysis":[14,37,43,122,140],"corpora.":[16],"We":[17],"propose":[18],"application":[20],"independent":[22,138],"component":[23,121,139],"analysis,":[24],"which":[25,83,131],"seems":[26],"have":[28,170],"clear":[29],"advantages":[30],"over":[31],"two":[32],"classic":[33],"methods:":[34],"latent":[35],"self-organizing":[39,107],"maps.":[40],"Latent":[41],"a":[45],"simple":[46],"method":[47],"for":[48,60,117],"automatic":[49],"generation":[50],"concepts":[52,66],"that":[53,145,168],"are":[54,146],"useful,":[55],"e.g.,":[56],"in":[57,95,102],"encoding":[58],"documents":[59],"information":[61],"retrieval":[62],"purposes.":[63],"However,":[64],"these":[65],"cannot":[67],"easily":[68,151],"be":[69,76,152,159],"interpreted":[70,153],"by":[71,154],"humans.":[72,155],"Self-organizing":[73],"maps":[74],"can":[75,150,158],"used":[77],"generate":[79],"an":[80],"explicit":[81,114,148],"diagram":[82],"characterizes":[84],"between":[87],"words.":[88,119],"The":[89,106],"resulting":[90],"map":[91,108],"reflects":[92],"categories":[94,101,116,144],"overall":[97],"organization":[98],"local":[104],"level.":[105],"does":[109],"not,":[110],"however,":[111],"provide":[112],"any":[113,162],"distinct":[115,129],"Independent":[120],"applied":[123],"word":[125],"context":[126],"data":[127],"gives":[128,141],"features":[130,142],"reflect":[132],"categories.":[136],"Thus,":[137],"or":[143,165,175],"both":[147],"This":[156],"result":[157],"obtained":[160],"without":[161],"human":[163],"supervision":[164],"tagged":[166],"corpora":[167],"would":[169],"some":[171],"predetermined":[172],"morphological,":[173],"information.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}