{"id":"https://openalex.org/W2005246064","doi":"https://doi.org/10.1109/cidm.2014.7008677","title":"Novelty detection applied to the classification problem using Probabilistic Neural Network","display_name":"Novelty detection applied to the classification problem using Probabilistic Neural Network","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2005246064","doi":"https://doi.org/10.1109/cidm.2014.7008677","mag":"2005246064"},"language":"en","primary_location":{"id":"doi:10.1109/cidm.2014.7008677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cidm.2014.7008677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","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/A5109116242","display_name":"Balvant Yadav","orcid":null},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Balvant Yadav","raw_affiliation_strings":["Department of Computer Science and Automation, Indian Institute of Science, Bangalore","Dept of Computer Science & Automation, Indian Institute of Science, Bangalore, India#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Indian Institute of Science, Bangalore","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Dept of Computer Science & Automation, Indian Institute of Science, Bangalore, India#TAB#","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101879348","display_name":"V. Susheela Devi","orcid":"https://orcid.org/0000-0003-1001-7714"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Susheela Devi","raw_affiliation_strings":["Department of Computer Science and Automation, Indian Institute of Science, Bangalore","Dept of Computer Science & Automation, Indian Institute of Science, Bangalore, India#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Automation, Indian Institute of Science, Bangalore","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Dept of Computer Science & Automation, Indian Institute of Science, Bangalore, India#TAB#","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4229,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.740138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"265","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9958999752998352,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/novelty-detection","display_name":"Novelty detection","score":0.8544540405273438},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.7521032691001892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7440445423126221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6739811301231384},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.642752468585968},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5901373624801636},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.57340407371521},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5498894453048706},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4951247274875641},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4628554880619049},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43151095509529114},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42608603835105896}],"concepts":[{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.8544540405273438},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.7521032691001892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7440445423126221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6739811301231384},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.642752468585968},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5901373624801636},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.57340407371521},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5498894453048706},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4951247274875641},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4628554880619049},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43151095509529114},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42608603835105896},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cidm.2014.7008677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cidm.2014.7008677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1490760466","https://openalex.org/W1968114659","https://openalex.org/W2005422315","https://openalex.org/W2016161382","https://openalex.org/W2042790056","https://openalex.org/W2081337758","https://openalex.org/W2118377301","https://openalex.org/W2126613216","https://openalex.org/W2134177842","https://openalex.org/W2134641333","https://openalex.org/W2146196597","https://openalex.org/W2153477625","https://openalex.org/W2154579312","https://openalex.org/W2169413195","https://openalex.org/W4240338048","https://openalex.org/W4244494905","https://openalex.org/W6679898850","https://openalex.org/W6681545543","https://openalex.org/W6682751323","https://openalex.org/W6682894622"],"related_works":["https://openalex.org/W2084551578","https://openalex.org/W3106061132","https://openalex.org/W2072135972","https://openalex.org/W2108287924","https://openalex.org/W2785731816","https://openalex.org/W2347912222","https://openalex.org/W2563096758","https://openalex.org/W4303627434","https://openalex.org/W4210977257","https://openalex.org/W2939647666"],"abstract_inverted_index":{"A":[0],"novel":[1,29,62,166],"pattern":[2,48,63,143,163],"is":[3,7,22,49,120,150],"an":[4,121],"observation":[5],"which":[6,27,119],"different":[8],"as":[9,60,164],"compared":[10],"to":[11,23,38,129,146,189],"the":[12,15,52,73,94,102,109,116,153,156],"rest":[13],"of":[14,19,72,155,197],"data.":[16],"The":[17],"task":[18],"novelty":[20,91,178,187],"detection":[21,179,188],"build":[24],"a":[25,32,43,47,61,126,141,147,165,194],"model":[26,36],"identifies":[28],"patterns":[30],"from":[31,51],"data":[33,105],"set.":[34],"This":[35],"has":[37],"be":[39,58,67],"built":[40],"in":[41],"such":[42,82],"way":[44],"that":[45,162],"if":[46,137],"distant":[50],"given":[53,74],"training":[54],"data,":[55],"it":[56,65],"should":[57,66],"classified":[59,68],"otherwise":[64],"into":[69],"any":[70],"one":[71],"classes.":[75],"In":[76,93,115],"this":[77],"paper,":[78],"we":[79,97,124,160,176,183],"present":[80,125],"two":[81],"new":[83,127],"models,":[84],"based":[85],"on":[86],"Probabilistic":[87],"Neural":[88],"Network":[89],"for":[90,133,140],"detection.":[92],"first":[95],"model,":[96,118,123],"generate":[98],"negative":[99,113],"examples":[100],"around":[101],"target":[103,148,157],"class":[104,135,149],"and":[106,136,181],"then":[107,159],"train":[108],"classifier":[110],"with":[111],"these":[112],"examples.":[114],"second":[117],"incremental":[122],"method":[128],"find":[130],"optimal":[131],"threshold":[132,154],"each":[134],"output":[138],"value":[139],"test":[142],"being":[144],"assigned":[145],"less":[151],"than":[152],"class,":[158],"classify":[161],"pattern.":[167],"We":[168,192],"show":[169,193],"how":[170],"decision":[171],"boundaries":[172],"are":[173],"created":[174],"when":[175,182],"add":[177,186],"mechanism":[180],"do":[184],"not":[185],"our":[190],"model.":[191],"comparative":[195],"performance":[196],"both":[198],"approaches.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
