{"id":"https://openalex.org/W2158704249","doi":"https://doi.org/10.1109/ijcnn.2010.5596539","title":"A method to build a representation using a classifier and its use in a K Nearest Neighbors-based deployment","display_name":"A method to build a representation using a classifier and its use in a K Nearest Neighbors-based deployment","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2158704249","doi":"https://doi.org/10.1109/ijcnn.2010.5596539","mag":"2158704249"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2010.5596539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2010.5596539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2010 International Joint Conference on Neural Networks (IJCNN)","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/A5103118554","display_name":"Vincent Lemaire","orcid":"https://orcid.org/0000-0002-6030-2356"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vincent Lemaire","raw_affiliation_strings":["Profiling and Datamining, Lannion, France","\u2018Profiling and Datamining\u2019, Lannion, France","'Profiling and Datamining', Lannion, France"],"affiliations":[{"raw_affiliation_string":"Profiling and Datamining, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"\u2018Profiling and Datamining\u2019, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"'Profiling and Datamining', Lannion, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111936967","display_name":"Marc Boull\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marc Boulle","raw_affiliation_strings":["Profiling and Datamining, Lannion, France","\u2018Profiling and Datamining\u2019, Lannion, France","'Profiling and Datamining', Lannion, France"],"affiliations":[{"raw_affiliation_string":"Profiling and Datamining, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"\u2018Profiling and Datamining\u2019, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"'Profiling and Datamining', Lannion, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087132141","display_name":"Fabrice Cl\u00e9rot","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fabrice Clerot","raw_affiliation_strings":["Profiling and Datamining, Lannion, France","\u2018Profiling and Datamining\u2019, Lannion, France","'Profiling and Datamining', Lannion, France"],"affiliations":[{"raw_affiliation_string":"Profiling and Datamining, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"\u2018Profiling and Datamining\u2019, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"'Profiling and Datamining', Lannion, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027517591","display_name":"Pascal Gouzien","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pascal Gouzien","raw_affiliation_strings":["Profiling and Datamining, Lannion, France","\u2018Profiling and Datamining\u2019, Lannion, France","'Profiling and Datamining', Lannion, France"],"affiliations":[{"raw_affiliation_string":"Profiling and Datamining, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"\u2018Profiling and Datamining\u2019, Lannion, France","institution_ids":[]},{"raw_affiliation_string":"'Profiling and Datamining', Lannion, France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103118554"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.451,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74701309,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"8","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9944000244140625,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9944000244140625,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.993399977684021,"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":0.9919000267982483,"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/closeness","display_name":"Closeness","score":0.8651893138885498},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7560949325561523},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.7312469482421875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7218620777130127},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6355900764465332},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6121591329574585},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4827098846435547},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45873773097991943},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.43793290853500366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4213683605194092},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4213332533836365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19739657640457153},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09293031692504883}],"concepts":[{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.8651893138885498},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7560949325561523},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.7312469482421875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7218620777130127},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6355900764465332},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6121591329574585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4827098846435547},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45873773097991943},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.43793290853500366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4213683605194092},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4213332533836365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19739657640457153},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09293031692504883},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2010.5596539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2010.5596539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2010 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W16536914","https://openalex.org/W49486804","https://openalex.org/W183657245","https://openalex.org/W568124517","https://openalex.org/W1502916507","https://openalex.org/W1510073064","https://openalex.org/W1563088657","https://openalex.org/W1625504505","https://openalex.org/W1678889691","https://openalex.org/W1760092048","https://openalex.org/W1784548050","https://openalex.org/W1922017469","https://openalex.org/W2001592424","https://openalex.org/W2108455851","https://openalex.org/W2113211233","https://openalex.org/W2119885577","https://openalex.org/W2128479019","https://openalex.org/W2129114758","https://openalex.org/W2163952039","https://openalex.org/W3000180494","https://openalex.org/W6601967094","https://openalex.org/W6607487446","https://openalex.org/W6629956336","https://openalex.org/W6636859864","https://openalex.org/W6640061767","https://openalex.org/W6676490248","https://openalex.org/W6679112488"],"related_works":["https://openalex.org/W2990663423","https://openalex.org/W2007713238","https://openalex.org/W3171568022","https://openalex.org/W2097149198","https://openalex.org/W2023878529","https://openalex.org/W3080558755","https://openalex.org/W2978680959","https://openalex.org/W4390606637","https://openalex.org/W260640599","https://openalex.org/W3123857158"],"abstract_inverted_index":{"The":[0,85],"K":[1],"Nearest":[2],"Neighbors":[3],"(KNN)":[4],"is":[5,25,48,69,77,91,111],"strongly":[6],"dependent":[7],"on":[8],"the":[9,12,20,32,49,55,60,66,95,98,105,116,119],"quality":[10],"of":[11,22,40,42,57,63,75,100,118],"distance":[13,29,50,102],"metric":[14,23,30,51],"used.":[15],"For":[16],"supervised":[17],"classification":[18],"problems,":[19],"aim":[21],"learning":[24],"to":[26,53,82,93,104,113,122],"learn":[27],"a":[28,37,71,80,101,108,123],"for":[31],"input":[33],"data":[34],"space":[35],"from":[36],"given":[38],"collection":[39],"pair":[41],"similar/dissimilar":[43],"points.":[44],"A":[45],"crucial":[46],"point":[47,68],"used":[52,92],"measure":[54],"closeness":[56],"instances.":[58],"In":[59],"industrial":[61],"context":[62],"this":[64,89],"paper":[65],"key":[67],"that":[70],"very":[72],"interesting":[73],"source":[74],"knowledge":[76,86],"available":[78],":":[79],"classifier":[81,90,120],"be":[83],"deployed.":[84],"incorporated":[87],"in":[88],"guide":[94],"choice":[96],"(or":[97],"construction)":[99],"adapted":[103],"situation":[106],"Then":[107],"KNN-based":[109],"deployment":[110,117],"elaborated":[112],"speed":[114],"up":[115],"compared":[121],"direct":[124],"deployment.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2015,"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"}