{"id":"https://openalex.org/W2108118693","doi":"https://doi.org/10.1109/ijcnn.2004.1381105","title":"Partially observed values","display_name":"Partially observed values","publication_year":2005,"publication_date":"2005-02-28","ids":{"openalex":"https://openalex.org/W2108118693","doi":"https://doi.org/10.1109/ijcnn.2004.1381105","mag":"2108118693"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1381105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381105","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/A5008894339","display_name":"Tapani Raiko","orcid":"https://orcid.org/0000-0002-0321-304X"},"institutions":[{"id":"https://openalex.org/I32943570","display_name":"Helsinki Institute for Information Technology","ror":"https://ror.org/05kph4940","country_code":"FI","type":"facility","lineage":["https://openalex.org/I133731052","https://openalex.org/I32943570","https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"T. Raiko","raw_affiliation_strings":["Laboratory of Computer and Information Science, Helsinki University of Technology, Espoo, Finland","Lab. of Computer and Information Science, Helsinki University of Technology, Espoo, Finland"],"affiliations":[{"raw_affiliation_string":"Laboratory of Computer and Information Science, Helsinki University of Technology, Espoo, Finland","institution_ids":["https://openalex.org/I32943570"]},{"raw_affiliation_string":"Lab. of Computer and Information Science, Helsinki University of Technology, Espoo, Finland","institution_ids":["https://openalex.org/I32943570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5008894339"],"corresponding_institution_ids":["https://openalex.org/I32943570"],"apc_list":null,"apc_paid":null,"fwci":1.6213,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84022101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"4","issue":null,"first_page":"2825","last_page":"2830"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9962999820709229,"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":0.9962999820709229,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9900000095367432,"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/preprocessor","display_name":"Preprocessor","score":0.7710140943527222},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.76155024766922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6364941000938416},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5861451029777527},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.568632185459137},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4948531985282898},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4939728379249573},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.451718807220459},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4508386552333832},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.44309747219085693},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.4406335651874542},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36819449067115784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3543189764022827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17185714840888977}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7710140943527222},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.76155024766922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6364941000938416},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5861451029777527},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.568632185459137},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4948531985282898},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4939728379249573},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.451718807220459},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4508386552333832},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.44309747219085693},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.4406335651874542},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36819449067115784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3543189764022827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17185714840888977}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn.2004.1381105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381105","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:10.1.1.156.1676","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.1676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.hut.fi/praiko/papers/ijcnn04poster.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.156.5950","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.5950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.hut.fi/praiko/papers/ijcnn04.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W33340904","https://openalex.org/W71499226","https://openalex.org/W179909587","https://openalex.org/W291356173","https://openalex.org/W1485014097","https://openalex.org/W1519041687","https://openalex.org/W1562345118","https://openalex.org/W1613284388","https://openalex.org/W1755360231","https://openalex.org/W1970655212","https://openalex.org/W1995880999","https://openalex.org/W2040665996","https://openalex.org/W2044758663","https://openalex.org/W2045656233","https://openalex.org/W2046495522","https://openalex.org/W2050127204","https://openalex.org/W2069114323","https://openalex.org/W2136226124","https://openalex.org/W2137969290","https://openalex.org/W2159080219","https://openalex.org/W2331052961","https://openalex.org/W2727071542","https://openalex.org/W3140073246","https://openalex.org/W3214201242","https://openalex.org/W4234789958","https://openalex.org/W4243367259","https://openalex.org/W4247690662","https://openalex.org/W4299670631","https://openalex.org/W6601379745","https://openalex.org/W6602928593","https://openalex.org/W6610472406","https://openalex.org/W6631171447","https://openalex.org/W6633904780","https://openalex.org/W6636241464","https://openalex.org/W6740346006"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2474028989"],"abstract_inverted_index":{"It":[0],"is":[1,46,61,73,95],"common":[2],"to":[3,87],"have":[4],"both":[5],"observed":[6,29],"and":[7,30,57],"missing":[8],"values":[9],"in":[10,42,55,63],"data.":[11,69,99],"This":[12],"paper":[13],"concentrates":[14],"on":[15],"the":[16,58,64,76,88],"case":[17],"where":[18],"a":[19,36,43,71,82,91],"value":[20],"can":[21],"be":[22],"somewhere":[23],"between":[24],"those":[25],"two":[26],"ends,":[27],"partially":[28,31],"missing.":[32],"To":[33],"achieve":[34],"that,":[35],"method":[37],"of":[38,50,80,85],"using":[39],"evidence":[40],"nodes":[41],"Bayesian":[44],"network":[45],"studied.":[47],"Different":[48],"ways":[49],"handling":[51],"inaccuracies":[52],"are":[53],"discussed":[54],"examples":[56],"proposed":[59],"approach":[60],"justified":[62],"experiments":[65],"with":[66],"real":[67],"image":[68],"Also,":[70],"justification":[72],"given":[74],"for":[75,97],"standard":[77],"preprocessing":[78],"step":[79],"adding":[81],"tiny":[83],"amount":[84],"noise":[86],"data,":[89],"when":[90],"continuous":[92],"valued":[93],"model":[94],"used":[96],"discrete-valued":[98]},"counts_by_year":[{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
