{"id":"https://openalex.org/W2145243650","doi":"https://doi.org/10.1109/ijcnn.2008.4634083","title":"Conditional information and information loss for flexible feature extraction","display_name":"Conditional information and information loss for flexible feature extraction","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2145243650","doi":"https://doi.org/10.1109/ijcnn.2008.4634083","mag":"2145243650"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5079603834","display_name":"Ryotaro Kamimura","orcid":"https://orcid.org/0000-0002-4238-3463"},"institutions":[{"id":"https://openalex.org/I1314466530","display_name":"Tokai University","ror":"https://ror.org/01p7qe739","country_code":"JP","type":"education","lineage":["https://openalex.org/I1314466530"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryotaro Kamimura","raw_affiliation_strings":["IT Education Center, Tokai University, Hiratsuka, Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"IT Education Center, Tokai University, Hiratsuka, Kanagawa, Japan","institution_ids":["https://openalex.org/I1314466530"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5079603834"],"corresponding_institution_ids":["https://openalex.org/I1314466530"],"apc_list":null,"apc_paid":null,"fwci":4.5764,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.9463538,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2074","last_page":"2083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9980000257492065,"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/T10320","display_name":"Neural Networks and Applications","score":0.9980000257492065,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9715999960899353,"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/T10057","display_name":"Face and Expression Recognition","score":0.942300021648407,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7378923892974854},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5884191989898682},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5564087629318237},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5153705477714539},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5102791786193848},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4627501964569092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44969871640205383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3772706687450409},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.349922239780426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13151779770851135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7378923892974854},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5884191989898682},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5564087629318237},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5153705477714539},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5102791786193848},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4627501964569092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44969871640205383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3772706687450409},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.349922239780426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13151779770851135},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1490454746","https://openalex.org/W1999110760","https://openalex.org/W2057973046","https://openalex.org/W2069451000","https://openalex.org/W2069667788","https://openalex.org/W2071781501","https://openalex.org/W2089657047","https://openalex.org/W2094015382","https://openalex.org/W2159110831","https://openalex.org/W2166810233","https://openalex.org/W2168487341","https://openalex.org/W2168993425","https://openalex.org/W2620711578","https://openalex.org/W6629419682"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2961085424","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W4224009465","https://openalex.org/W2256933480","https://openalex.org/W3018365851","https://openalex.org/W4306674287"],"abstract_inverted_index":{"In":[0,107],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,48,96,99,104],"new":[6],"information-theoretic":[7,18],"approach":[8],"to":[9,27,40,89],"competitive":[10,49],"learning":[11],"and":[12,24,79,103],"self-organizing":[13],"maps.":[14],"We":[15,85],"use":[16],"several":[17],"measures":[19],"such":[20],"as":[21],"conditional":[22,35],"information":[23,25,36,44,56,64,67,74,80],"losses":[26],"extract":[28],"main":[29,114],"features":[30,115],"in":[31,47,58,116],"input":[32,53,77,83,117],"patterns.":[33],"First,":[34],"content":[37,57],"is":[38,45,61,69],"used":[39],"show":[41],"how":[42],"much":[43],"contained":[46],"unit":[50],"or":[51],"an":[52,82,90],"pattern.":[54],"Then,":[55],"each":[59],"variable":[60],"detected":[62],"by":[63,71],"losses.":[65],"The":[66],"loss":[68],"defined":[70],"difference":[72],"between":[73],"with":[75],"all":[76,108],"units":[78],"without":[81],"unit.":[84],"applied":[86],"the":[87,93],"method":[88],"artificial":[91],"data,":[92],"Iris":[94],"problem,":[95],"student":[97],"survey,":[98],"CPU":[100],"classification":[101],"problem":[102],"company":[105],"survey.":[106],"cases,":[109],"experimental":[110],"results":[111],"showed":[112],"that":[113],"patterns":[118],"were":[119],"clearly":[120],"detected.":[121]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}